dylanhogg/awesome-python · Datasets at Hugging Face

1,466

util

https://github.com/lcompilers/lpython

[]

null

[]

null

lcompilers/lpython

lpython

1,175

122

28

C++

https://lpython.org/

Python compiler

lcompilers

2024-01-12

2021-12-29

108

10.793963

https://avatars.githubusercontent.com/u/96538276?v=4

Python compiler

['compiler', 'high-performance']

2024-01-11

[('exaloop/codon', 0.7257847189903259, 'perf', 2), ('cython/cython', 0.6913489699363708, 'util', 0), ('pypy/pypy', 0.6041545271873474, 'util', 1), ('numba/numba', 0.603155255317688, 'perf', 1), ('pyston/pyston', 0.6024731397628784, 'util', 0), ('klen/py-frameworks-bench', 0.587522566318512, 'perf', 0), ('markshannon/faster-cpython', 0.5289682149887085, 'perf', 0), ('faster-cpython/tools', 0.5253562927246094, 'perf', 0), ('numba/llvmlite', 0.5191760063171387, 'util', 0), ('fastai/fastcore', 0.5177335739135742, 'util', 0), ('pympler/pympler', 0.5168886184692383, 'perf', 0), ('p403n1x87/austin', 0.5144882798194885, 'profiling', 0), ('benfred/py-spy', 0.5141026377677917, 'profiling', 0), ('pyutils/line_profiler', 0.5114628076553345, 'profiling', 0), ('joblib/joblib', 0.5082236528396606, 'util', 0), ('google/jax', 0.5010378956794739, 'ml', 0)]

65

6

null

30.87

97

58

25

0

11

12

11

97

217

90

2.2

55

1,835

llm

https://github.com/hao-ai-lab/lookaheaddecoding

['decoding', 'lookahead']

Break the Sequential Dependency of LLM Inference Using Lookahead Decoding

[]

null

hao-ai-lab/lookaheaddecoding

LookaheadDecoding

802

49

9

Python

null

hao-ai-lab

2024-01-14

2023-11-21

10

80.2

https://avatars.githubusercontent.com/u/149045815?v=4

Break the Sequential Dependency of LLM Inference Using Lookahead Decoding

[]

['decoding', 'lookahead']

2024-01-09

[('karpathy/llama2.c', 0.5412218570709229, 'llm', 0), ('facebookresearch/llama', 0.5299458503723145, 'llm', 0), ('artidoro/qlora', 0.5174603462219238, 'llm', 0), ('facebookresearch/codellama', 0.5007719397544861, 'llm', 0)]

5

2

null

0.31

44

24

2

0

44

175

90

4

55

499

ml

https://github.com/ageron/handson-ml2

[]

null

[]

null

ageron/handson-ml2

handson-ml2

26,281

12,333

648

Jupyter Notebook

null

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

ageron

2024-01-14

2019-01-08

264

99.549242

null

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

[]

2023-02-04

[('fchollet/deep-learning-with-python-notebooks', 0.8291416168212891, 'study', 0), ('jakevdp/pythondatasciencehandbook', 0.6813152432441711, 'study', 0), ('gradio-app/gradio', 0.6595058441162109, 'viz', 0), ('rasbt/machine-learning-book', 0.6461301445960999, 'study', 0), ('firmai/industry-machine-learning', 0.6424956321716309, 'study', 0), ('mrdbourke/pytorch-deep-learning', 0.633056104183197, 'study', 0), ('wesm/pydata-book', 0.6252664923667908, 'study', 0), ('pytorch/ignite', 0.6152977347373962, 'ml-dl', 0), ('probml/pyprobml', 0.6119535565376282, 'ml', 0), ('scikit-learn/scikit-learn', 0.6084038615226746, 'ml', 0), ('intel/intel-extension-for-pytorch', 0.6076744198799133, 'perf', 0), ('ddbourgin/numpy-ml', 0.6011914014816284, 'ml', 0), ('uber/petastorm', 0.5999022126197815, 'data', 0), ('skorch-dev/skorch', 0.5958633422851562, 'ml-dl', 0), ('jupyter/nbformat', 0.5934438705444336, 'jupyter', 0), ('cohere-ai/notebooks', 0.5897052884101868, 'llm', 0), ('d2l-ai/d2l-en', 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('mdbloice/augmentor', 0.5503374338150024, 'ml', 0), ('graykode/nlp-tutorial', 0.5493988394737244, 'study', 0), ('tensorflow/lucid', 0.5488042235374451, 'ml-interpretability', 0), ('tensorflow/tensor2tensor', 0.5483447313308716, 'ml', 0), ('dmlc/dgl', 0.5474348068237305, 'ml-dl', 0), ('patchy631/machine-learning', 0.5471069812774658, 'ml', 0), ('lightly-ai/lightly', 0.5470166802406311, 'ml', 0), ('kubeflow-kale/kale', 0.5455378293991089, 'ml-ops', 0), ('ipython/ipyparallel', 0.5427348017692566, 'perf', 0), ('pycaret/pycaret', 0.5426246523857117, 'ml', 0), ('keras-rl/keras-rl', 0.5413088202476501, 'ml-rl', 0), ('huggingface/transformers', 0.5403335094451904, 'nlp', 0), ('udlbook/udlbook', 0.539566159248352, 'study', 0), ('jupyter/nbconvert', 0.5394284725189209, 'jupyter', 0), ('tlkh/tf-metal-experiments', 0.5388534665107727, 'perf', 0), ('aws/sagemaker-python-sdk', 0.5365365743637085, 'ml', 0), ('gerdm/prml', 0.5364505648612976, 'study', 0), ('arogozhnikov/einops', 0.5353853702545166, 'ml-dl', 0), ('wandb/client', 0.5327136516571045, 'ml', 0), ('automl/auto-sklearn', 0.531454861164093, 'ml', 0), ('scikit-learn-contrib/metric-learn', 0.5313714146614075, 'ml', 0), ('tensorflow/addons', 0.5312256813049316, 'ml', 0), ('dylanhogg/awesome-python', 0.5303460955619812, 'study', 0), ('mynameisfiber/high_performance_python_2e', 0.5303263068199158, 'study', 0), ('goldmansachs/gs-quant', 0.5294873118400574, 'finance', 0), ('koaning/human-learn', 0.5293908715248108, 'data', 0), ('keras-team/keras-nlp', 0.528778076171875, 'nlp', 0), ('cerlymarco/medium_notebook', 0.525178074836731, 'study', 0), ('xl0/lovely-numpy', 0.52412348985672, 'util', 0), ('pyro-ppl/pyro', 0.522969663143158, 'ml-dl', 0), ('adafruit/circuitpython', 0.5219725966453552, 'util', 0), ('rafiqhasan/auto-tensorflow', 0.5208608508110046, 'ml-dl', 0), ('jupyter/notebook', 0.5203615427017212, 'jupyter', 0), ('skops-dev/skops', 0.5202804207801819, 'ml-ops', 0), ('epistasislab/tpot', 0.5202245712280273, 'ml', 0), ('aws/graph-notebook', 0.519343912601471, 'jupyter', 0), ('ta-lib/ta-lib-python', 0.5182675123214722, 'finance', 0), ('horovod/horovod', 0.5166817307472229, 'ml-ops', 0), ('rasbt/stat451-machine-learning-fs20', 0.5153390169143677, 'study', 0), ('koaning/scikit-lego', 0.5152604579925537, 'ml', 0), ('pyg-team/pytorch_geometric', 0.5134172439575195, 'ml-dl', 0), ('huggingface/datasets', 0.5119935870170593, 'nlp', 0), ('explosion/thinc', 0.5114274621009827, 'ml-dl', 0), ('scikit-learn-contrib/lightning', 0.5109522938728333, 'ml', 0), ('jupyterlab/jupyterlab-desktop', 0.510633647441864, 'jupyter', 0), ('nicolas-chaulet/torch-points3d', 0.5103498101234436, 'ml', 0), ('jupyter/nbgrader', 0.5094665884971619, 'jupyter', 0), ('quantopian/qgrid', 0.5087634921073914, 'jupyter', 0), ('google/gin-config', 0.5084095001220703, 'util', 0), ('python/cpython', 0.5082079172134399, 'util', 0), ('microsoft/flaml', 0.5074008107185364, 'ml', 0), ('pypy/pypy', 0.5072569251060486, 'util', 0), ('eleutherai/pyfra', 0.5071380734443665, 'ml', 0), ('tatsu-lab/stanford_alpaca', 0.5068382620811462, 'llm', 0), ('jupyter-widgets/ipywidgets', 0.5040411949157715, 'jupyter', 0), ('realpython/python-guide', 0.5025880336761475, 'study', 0), ('iryna-kondr/scikit-llm', 0.5018590688705444, 'llm', 0), ('jupyterlab/jupyterlab', 0.5005123019218445, 'jupyter', 0), ('google/vizier', 0.5004328489303589, 'ml', 0)]

75

2

null

0.04

6

2

61

11

0

6

7

90

1.2

54

671

ml-dl

https://github.com/facebookresearch/detectron

[]

null

[]

null

facebookresearch/detectron

Detectron

26,066

5,568

944

Python

null

FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.

facebookresearch

2024-01-14

2017-10-05

329

79.056326

https://avatars.githubusercontent.com/u/16943930?v=4

FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.

[]

2023-10-19

[('matterport/mask_rcnn', 0.5304756760597229, 'ml-dl', 0), ('open-mmlab/mmdetection', 0.5015984177589417, 'ml', 0)]

43

3

null

0.12

2

0

76

3

0

2

90

1

54

1,243

ml

https://github.com/jindongwang/transferlearning

[]

null

[]

null

jindongwang/transferlearning

transferlearning

12,474

3,731

336

Python

http://transferlearning.xyz/

Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习

jindongwang

2024-01-14

2017-04-30

352

35.408759

null

Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习

['deep-learning', 'domain-adaptation', 'domain-adaption', 'domain-generalization', 'few-shot', 'few-shot-learning', 'generalization', 'machine-learning', 'meta-learning', 'paper', 'papers', 'representation-learning', 'self-supervised-learning', 'style-transfer', 'survey', 'theory', 'transfer-learning', 'transferlearning', 'tutorial-code', 'unsupervised-learning']

2024-01-08

[('amanchadha/coursera-deep-learning-specialization', 0.5513812899589539, 'study', 1), ('huggingface/autotrain-advanced', 0.5214440822601318, 'ml', 2), ('patchy631/machine-learning', 0.5060864090919495, 'ml', 0), ('alirezadir/machine-learning-interview-enlightener', 0.5019001364707947, 'study', 2), ('udacity/deep-learning-v2-pytorch', 0.501124918460846, 'study', 2), ('awslabs/autogluon', 0.5002632141113281, 'ml', 3)]

40

4

null

0.96

14

7

82

0

14

22

90

1.6

54

425

ml-dl

https://github.com/facebookresearch/detr

[]

null

[]

null

facebookresearch/detr

detr

12,338

2,222

149

Python

null

End-to-End Object Detection with Transformers

facebookresearch

2024-01-14

2020-05-26

192

64.260417

https://avatars.githubusercontent.com/u/16943930?v=4

End-to-End Object Detection with Transformers

[]

2023-02-07

[('cvg/lightglue', 0.5226452350616455, 'ml-dl', 0), ('nvlabs/gcvit', 0.5166937112808228, 'diffusion', 0), ('matterport/mask_rcnn', 0.5123329758644104, 'ml-dl', 0)]

26

7

null

0.02

36

7

44

11

0

36

47

90

1.3

54

1,380

ml

https://github.com/microsoft/swin-transformer

[]

null

[]

null

microsoft/swin-transformer

Swin-Transformer

12,319

1,937

125

Python

https://arxiv.org/abs/2103.14030

This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".

microsoft

2024-01-14

2021-03-25

148

82.836695

https://avatars.githubusercontent.com/u/6154722?v=4

This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".

['ade20k', 'image-classification', 'imagenet', 'mask-rcnn', 'mscoco', 'object-detection', 'semantic-segmentation', 'swin-transformer']

2023-08-16

[('nvlabs/gcvit', 0.6548908352851868, 'diffusion', 4), ('google-research/maxvit', 0.5897934436798096, 'ml', 1), ('lucidrains/vit-pytorch', 0.5670905113220215, 'ml-dl', 1), ('open-mmlab/mmdetection', 0.5538708567619324, 'ml', 3), ('deci-ai/super-gradients', 0.5506076812744141, 'ml-dl', 4), ('open-mmlab/mmsegmentation', 0.5363519191741943, 'ml', 2), ('hrnet/hrnet-semantic-segmentation', 0.5201693177223206, 'ml', 1), ('roboflow/supervision', 0.5062756538391113, 'ml', 1)]

13

8

null

0.02

20

3

34

5

0

20

11

90

0.6

54

85

ml

https://github.com/statsmodels/statsmodels

[]

null

[]

null

statsmodels/statsmodels

statsmodels

9,210

2,836

279

Python

http://www.statsmodels.org/devel/

Statsmodels: statistical modeling and econometrics in Python

statsmodels

2024-01-13

2011-06-12

659

13.969664

https://avatars.githubusercontent.com/u/717666?v=4

Statsmodels: statistical modeling and econometrics in Python

['count-model', 'data-analysis', 'data-science', 'econometrics', 'forecasting', 'generalized-linear-models', 'hypothesis-testing', 'prediction', 'regression-models', 'robust-estimation', 'statistics', 'timeseries-analysis']

2024-01-04

[('firmai/atspy', 0.6599208116531372, 'time-series', 1), ('ranaroussi/quantstats', 0.6285594701766968, 'finance', 0), ('alkaline-ml/pmdarima', 0.6218242645263672, 'time-series', 2), ('scikit-learn/scikit-learn', 0.6116586327552795, 'ml', 3), ('scikit-mobility/scikit-mobility', 0.5975031852722168, 'gis', 3), ('bashtage/arch', 0.5926198363304138, 'time-series', 1), ('plotly/dash', 0.5885524749755859, 'viz', 1), ('awslabs/gluonts', 0.5710023641586304, 'time-series', 2), ('goldmansachs/gs-quant', 0.5688977241516113, 'finance', 0), ('pymc-devs/pymc3', 0.5598034858703613, 'ml', 0), ('uber/orbit', 0.5589537024497986, 'time-series', 2), ('stan-dev/pystan', 0.5519436001777649, 'ml', 0), ('quantecon/quantecon.py', 0.5498467087745667, 'sim', 0), ('pandas-dev/pandas', 0.5481253266334534, 'pandas', 2), ('rjt1990/pyflux', 0.5408421158790588, 'time-series', 1), ('crflynn/stochastic', 0.5304479002952576, 'sim', 0), ('online-ml/river', 0.5298870205879211, 'ml', 1), ('krzjoa/awesome-python-data-science', 0.5274232625961304, 'study', 3), ('rasbt/mlxtend', 0.5218582153320312, 'ml', 1), ('eleutherai/pyfra', 0.5143864154815674, 'ml', 0), ('polyaxon/datatile', 0.5121821165084839, 'pandas', 2), ('wesm/pydata-book', 0.5118904709815979, 'study', 0), ('cuemacro/finmarketpy', 0.5101310610771179, 'finance', 0)]

421

2

null

6.69

232

140

153

0

3

4

3

232

184

90

0.8

54

528

util

https://github.com/facebookresearch/hydra

[]

null

[]

null

facebookresearch/hydra

hydra

7,864

616

124

Python

https://hydra.cc

Hydra is a framework for elegantly configuring complex applications

facebookresearch

2024-01-14

2019-06-12

241

32.515062

https://avatars.githubusercontent.com/u/16943930?v=4

Hydra is a framework for elegantly configuring complex applications

[]

2023-11-30

[('ashleve/lightning-hydra-template', 0.5850319266319275, 'util', 0), ('google/gin-config', 0.5556942224502563, 'util', 0), ('willmcgugan/textual', 0.5213847160339355, 'term', 0), ('alphasecio/langchain-examples', 0.5024363994598389, 'llm', 0)]

114

3

null

0.63

69

20

56

2

1

5

1

69

142

90

2.1

54

1,192

util

https://github.com/xonsh/xonsh

['shell']

null

[]

null

xonsh/xonsh

xonsh

7,471

633

105

Python

http://xon.sh

:shell: Python-powered, cross-platform, Unix-gazing shell.

xonsh

2024-01-14

2015-01-21

470

15.866808

https://avatars.githubusercontent.com/u/17418188?v=4

:shell: Python-powered, cross-platform, Unix-gazing shell.

['bash', 'cli', 'command-line', 'console', 'devops', 'fish', 'iterm2', 'prompt', 'python-shell', 'script', 'shell', 'terminal', 'windows-terminal', 'xonsh', 'zsh']

2023-12-31

[('tiangolo/typer', 0.614140510559082, 'term', 3), ('kellyjonbrazil/jc', 0.5756747722625732, 'util', 3), ('jquast/blessed', 0.569438099861145, 'term', 2), ('pygamelib/pygamelib', 0.5624502301216125, 'gamedev', 0), ('urwid/urwid', 0.5422582030296326, 'term', 0), ('pypy/pypy', 0.5222761631011963, 'util', 0), ('tmbo/questionary', 0.5194598436355591, 'term', 1), ('python/cpython', 0.5193564891815186, 'util', 0), ('federicoceratto/dashing', 0.5140331387519836, 'term', 1), ('google/python-fire', 0.5076464414596558, 'term', 1), ('evhub/coconut', 0.5075111985206604, 'util', 1), ('hoffstadt/dearpygui', 0.504555881023407, 'gui', 0), ('cython/cython', 0.5044435262680054, 'util', 0)]

320

2

null

1.9

64

34

109

0

4

14

4

64

118

90

1.8

54

1,274

util

https://github.com/googleapis/google-api-python-client

[]

null

[]

null

googleapis/google-api-python-client

google-api-python-client

7,135

2,452

284

Python

https://googleapis.github.io/google-api-python-client/docs/

🐍 The official Python client library for Google's discovery based APIs.

googleapis

2024-01-13

2014-01-08

524

13.594175

https://avatars.githubusercontent.com/u/16785467?v=4

🐍 The official Python client library for Google's discovery based APIs.

[]

2024-01-09

[('nv7-github/googlesearch', 0.6702570915222168, 'util', 0), ('dsdanielpark/bard-api', 0.6036682724952698, 'llm', 0), ('openai/openai-python', 0.5968145728111267, 'util', 0), ('dialogflow/dialogflow-python-client-v2', 0.5611771941184998, 'nlp', 0), ('radiantearth/radiant-mlhub', 0.5603718757629395, 'gis', 0), ('typesense/typesense-python', 0.5588173866271973, 'data', 0), ('snyk-labs/pysnyk', 0.5522992610931396, 'security', 0), ('psf/requests', 0.552095353603363, 'web', 0), ('jovianml/opendatasets', 0.551531970500946, 'data', 0), ('meilisearch/meilisearch-python', 0.5505169034004211, 'data', 0), ('googleapis/python-speech', 0.5471388101577759, 'ml', 0), ('pytoolz/toolz', 0.5453507304191589, 'util', 0), ('urwid/urwid', 0.54488605260849, 'term', 0), ('simple-salesforce/simple-salesforce', 0.541388213634491, 'data', 0), ('qdrant/qdrant-client', 0.5371494293212891, 'util', 0), ('giswqs/geemap', 0.5369963645935059, 'gis', 0), ('scholarly-python-package/scholarly', 0.5367330312728882, 'data', 0), ('requests/toolbelt', 0.5348877906799316, 'util', 0), ('clips/pattern', 0.5339103937149048, 'nlp', 0), ('fastai/ghapi', 0.5308494567871094, 'util', 0), ('huggingface/huggingface_hub', 0.5284603238105774, 'ml', 0), ('shishirpatil/gorilla', 0.524009108543396, 'llm', 0), ('goldsmith/wikipedia', 0.5227052569389343, 'data', 0), ('mitmproxy/pdoc', 0.5224719047546387, 'util', 0), ('hydrosquall/tiingo-python', 0.5202198624610901, 'finance', 0), ('pndurette/gtts', 0.5190337300300598, 'util', 0), ('landscapeio/prospector', 0.5145336389541626, 'util', 0), ('googleapis/python-bigquery', 0.5121608376502991, 'data', 0), ('amaargiru/pyroad', 0.5120947957038879, 'study', 0), ('hugapi/hug', 0.5113233327865601, 'util', 0), ('serpapi/google-search-results-python', 0.5091744065284729, 'util', 0), ('scrapy/scrapy', 0.5074482560157776, 'data', 0), ('cohere-ai/cohere-python', 0.5053079128265381, 'util', 0), ('1200wd/bitcoinlib', 0.5004116892814636, 'crypto', 0)]

190

3

null

2.69

79

55

122

0

41

18

41

77

84

90

1.1

54

44

ml

https://github.com/lmcinnes/umap

[]

null

[]

null

lmcinnes/umap

umap

6,678

754

128

Python

null

Uniform Manifold Approximation and Projection

lmcinnes

2024-01-14

2017-07-02

343

19.453184

null

Uniform Manifold Approximation and Projection

['dimensionality-reduction', 'machine-learning', 'topological-data-analysis', 'umap', 'visualization']

2024-01-08

[('geomstats/geomstats', 0.5977250933647156, 'math', 1)]

128

7

null

1.29

30

8

80

0

2

4

2

30

36

90

1.2

54

194

util

https://github.com/pycqa/isort

['code-quality']

null

[]

null

pycqa/isort

isort

6,190

604

48

Python

https://pycqa.github.io/isort/

A Python utility / library to sort imports.

pycqa

2024-01-14

2013-09-02

543

11.396633

https://avatars.githubusercontent.com/u/8749848?v=4

A Python utility / library to sort imports.

['auto-formatter', 'cleaner', 'cli', 'formatter', 'isort', 'linter', 'python-utility', 'sorting-imports']

['auto-formatter', 'cleaner', 'cli', 'code-quality', 'formatter', 'isort', 'linter', 'python-utility', 'sorting-imports']

2024-01-12

[('hadialqattan/pycln', 0.6549221277236938, 'util', 0), ('google/yapf', 0.5961623191833496, 'util', 2), ('asottile/reorder-python-imports', 0.5951371192932129, 'util', 2), ('landscapeio/prospector', 0.574863851070404, 'util', 0), ('sethmmorton/natsort', 0.5276709794998169, 'util', 0), ('google/pytype', 0.5101639032363892, 'typing', 2), ('hhatto/autopep8', 0.5075655579566956, 'util', 1), ('grantjenks/blue', 0.5017447471618652, 'util', 2)]

294

7

null

1.38

53

33

126

0

5

14

5

53

75

90

1.4

54

741

study

https://github.com/zhanymkanov/fastapi-best-practices

[]

null

[]

null

zhanymkanov/fastapi-best-practices

fastapi-best-practices

5,917

449

91

null

FastAPI Best Practices and Conventions we used at our startup

zhanymkanov

2024-01-14

2022-08-09

77

76.844156

null

FastAPI Best Practices and Conventions we used at our startup

['best-practices', 'fastapi']

2023-10-22

[('fastapi-users/fastapi-users', 0.6014936566352844, 'web', 1), ('asacristani/fastapi-rocket-boilerplate', 0.5217467546463013, 'template', 1), ('dmontagu/fastapi_client', 0.5196253061294556, 'web', 0), ('tiangolo/fastapi', 0.5182605981826782, 'web', 1)]

10

5

null

0.21

5

2

17

3

0

5

11

90

2.2

54

369

time-series

https://github.com/facebookresearch/kats

['time-series']

null

[]

null

facebookresearch/kats

Kats

4,647

508

77

Python

null

Kats, a kit to analyze time series data, a lightweight, easy-to-use, generalizable, and extendable framework to perform time series analysis, from understanding the key statistics and characteristics, detecting change points and anomalies, to forecasting future trends.

facebookresearch

2024-01-14

2021-02-25

152

30.429373

https://avatars.githubusercontent.com/u/16943930?v=4

Kats, a kit to analyze time series data, a lightweight, easy-to-use, generalizable, and extendable framework to perform time series analysis, from understanding the key statistics and characteristics, detecting change points and anomalies, to forecasting future trends.

[]

['time-series']

2024-01-10

[('sktime/sktime', 0.5305997729301453, 'time-series', 1), ('alkaline-ml/pmdarima', 0.5154160261154175, 'time-series', 1), ('salesforce/merlion', 0.5117724537849426, 'time-series', 1)]

136

4

null

1.75

8

4

35

0

1

8

12

90

1.5

54

380

ml-ops

https://github.com/aimhubio/aim

[]

null

[]

null

aimhubio/aim

aim

4,468

274

45

Python

https://aimstack.io

Aim 💫 — An easy-to-use & supercharged open-source experiment tracker.

aimhubio

2024-01-13

2019-05-31

243

18.343695

https://avatars.githubusercontent.com/u/51399196?v=4

Aim 💫 — An easy-to-use & supercharged open-source experiment tracker.

['ai', 'data-science', 'data-visualization', 'experiment-tracking', 'machine-learning', 'metadata', 'metadata-tracking', 'ml', 'mlflow', 'mlops', 'prompt-engineering', 'pytorch', 'tensorboard', 'tensorflow', 'visualization']

2024-01-12

[('wandb/client', 0.696733832359314, 'ml', 5), ('polyaxon/datatile', 0.6386370062828064, 'pandas', 5), ('determined-ai/determined', 0.614514172077179, 'ml-ops', 5), ('netflix/metaflow', 0.5948770046234131, 'ml-ops', 5), ('mlflow/mlflow', 0.5842969417572021, 'ml-ops', 4), ('iterative/dvc', 0.5769718885421753, 'ml-ops', 3), ('whylabs/whylogs', 0.5764767527580261, 'util', 3), ('salesforce/logai', 0.5716543197631836, 'util', 2), ('microsoft/onnxruntime', 0.5700400471687317, 'ml', 3), ('transformeroptimus/superagi', 0.5632416605949402, 'llm', 1), ('polyaxon/polyaxon', 0.5590616464614868, 'ml-ops', 6), ('activeloopai/deeplake', 0.5577347874641418, 'ml-ops', 7), ('nebuly-ai/nebullvm', 0.5485852360725403, 'perf', 1), ('alirezadir/machine-learning-interview-enlightener', 0.5477184653282166, 'study', 2), ('huggingface/datasets', 0.5470335483551025, 'nlp', 3), ('bentoml/bentoml', 0.5450233817100525, 'ml-ops', 3), ('tensorflow/tensorflow', 0.5438287258148193, 'ml-dl', 3), ('doccano/doccano', 0.5435435771942139, 'nlp', 1), ('prefecthq/marvin', 0.541201114654541, 'nlp', 1), ('sweepai/sweep', 0.5406528115272522, 'llm', 1), ('googlecloudplatform/vertex-ai-samples', 0.5386273264884949, 'ml', 4), ('oegedijk/explainerdashboard', 0.5350830554962158, 'ml-interpretability', 0), ('roboflow/supervision', 0.5213971138000488, 'ml', 3), ('argilla-io/argilla', 0.5164137482643127, 'nlp', 3), ('adap/flower', 0.5154430270195007, 'ml-ops', 4), ('merantix-momentum/squirrel-core', 0.5153231024742126, 'ml', 6), ('csinva/imodels', 0.5152265429496765, 'ml', 4), ('cheshire-cat-ai/core', 0.5146742463111877, 'llm', 1), ('tensorlayer/tensorlayer', 0.5126657485961914, 'ml-rl', 1), ('gradio-app/gradio', 0.5126237869262695, 'viz', 3), ('kedro-org/kedro-viz', 0.5116142630577087, 'ml-ops', 2), ('mlc-ai/mlc-llm', 0.509802520275116, 'llm', 0), ('bulletphysics/bullet3', 0.5082801580429077, 'sim', 0), ('pathwaycom/llm-app', 0.506819486618042, 'llm', 1), ('google-research/language', 0.5032878518104553, 'nlp', 1), ('fmind/mlops-python-package', 0.5028169751167297, 'template', 3), ('laion-ai/open-assistant', 0.5019581913948059, 'llm', 2), ('pytorchlightning/pytorch-lightning', 0.5019053220748901, 'ml-dl', 4), ('tlkh/tf-metal-experiments', 0.501725971698761, 'perf', 1)]

58

4

null

2.5

79

29

56

0

9

36

9

79

91

90

1.2

54

1,552

study

https://github.com/neetcode-gh/leetcode

['interview-questions', 'data-structures', 'leetcode']

Leetcode solutions for NeetCode.io

[]

null

neetcode-gh/leetcode

leetcode

4,459

2,046

40

JavaScript

null

Leetcode solutions

neetcode-gh

2024-01-14

2021-01-20

157

28.247059

null

Leetcode solutions

[]

['data-structures', 'interview-questions', 'leetcode']

2024-01-13

[('mdmzfzl/neetcode-solutions', 0.6274089217185974, 'study', 3)]

612

1

null

34.92

182

100

36

0

181

51

90

0.3

54

353

ml-interpretability

https://github.com/pytorch/captum

[]

null

[]

null

pytorch/captum

captum

4,372

469

225

Python

https://captum.ai

Model interpretability and understanding for PyTorch

pytorch

2024-01-14

2019-08-27

231

18.926407

https://avatars.githubusercontent.com/u/21003710?v=4

Model interpretability and understanding for PyTorch

['feature-attribution', 'feature-importance', 'interpretability', 'interpretable-ai', 'interpretable-ml']

2024-01-08

[('pytorch/ignite', 0.6821672916412354, 'ml-dl', 0), ('tensorflow/lucid', 0.6784272193908691, 'ml-interpretability', 1), ('csinva/imodels', 0.6309248208999634, 'ml', 1), ('skorch-dev/skorch', 0.6131489276885986, 'ml-dl', 0), ('interpretml/interpret', 0.6127338409423828, 'ml-interpretability', 3), ('mrdbourke/pytorch-deep-learning', 0.5934852361679077, 'study', 0), ('allenai/allennlp', 0.5909707546234131, 'nlp', 0), ('marcotcr/lime', 0.5743399262428284, 'ml-interpretability', 1), ('intel/intel-extension-for-pytorch', 0.5694814324378967, 'perf', 0), ('pair-code/lit', 0.5618991851806641, 'ml-interpretability', 0), ('nvidia/apex', 0.5534337759017944, 'ml-dl', 0), ('eleutherai/pythia', 0.5508965253829956, 'ml-interpretability', 2), ('xl0/lovely-tensors', 0.5507166385650635, 'ml-dl', 0), ('huggingface/transformers', 0.5457330942153931, 'nlp', 0), ('huggingface/accelerate', 0.5386924743652344, 'ml', 0), ('pytorch/data', 0.5359891057014465, 'data', 0), ('selfexplainml/piml-toolbox', 0.5324576497077942, 'ml-interpretability', 0), ('rasbt/machine-learning-book', 0.5297553539276123, 'study', 0), ('arogozhnikov/einops', 0.524075984954834, 'ml-dl', 0), ('ibm/transition-amr-parser', 0.5239638090133667, 'nlp', 0), ('hysts/pytorch_image_classification', 0.5230705142021179, 'ml-dl', 0), ('mosaicml/composer', 0.5189915299415588, 'ml-dl', 0), ('speechbrain/speechbrain', 0.5150958895683289, 'nlp', 0), ('pytorch/rl', 0.5139393210411072, 'ml-rl', 0), ('rafiqhasan/auto-tensorflow', 0.5135285258293152, 'ml-dl', 0), ('rentruewang/koila', 0.5131102800369263, 'ml', 0), ('salesforce/blip', 0.5107000470161438, 'diffusion', 0), ('ashleve/lightning-hydra-template', 0.5099735260009766, 'util', 0), ('pytorch/botorch', 0.509192168712616, 'ml-dl', 0), ('blackhc/toma', 0.5078623294830322, 'ml-dl', 0), ('seldonio/alibi', 0.5067712664604187, 'ml-interpretability', 1), ('cvxgrp/pymde', 0.5022547245025635, 'ml', 0)]

104

3

null

1

61

40

53

0

1

2

1

61

181

90

3

54

604

testing

https://github.com/seleniumbase/seleniumbase

[]

null

[]

null

seleniumbase/seleniumbase

SeleniumBase

3,859

871

125

Python

https://seleniumbase.io

Browser automation framework for testing with Selenium, Python, and pytest. Includes a Dashboard, a Recorder for generating tests, Undetected Mode, and more.

seleniumbase

2024-01-13

2014-03-04

517

7.464217

https://avatars.githubusercontent.com/u/17287301?v=4

Browser automation framework for testing with Selenium, Python, and pytest. Includes a Dashboard, a Recorder for generating tests, Undetected Mode, and more.

['behave', 'chrome', 'chromedriver', 'e2e-testing', 'firefox', 'pytest', 'pytest-plugin', 'selenium', 'selenium-python', 'seleniumbase', 'test', 'unittests', 'web-automation', 'webdriver', 'webkit']

2024-01-04

[('cobrateam/splinter', 0.7703961730003357, 'testing', 2), ('microsoft/playwright-python', 0.6941218972206116, 'testing', 2), ('webpy/webpy', 0.5600611567497253, 'web', 0), ('taverntesting/tavern', 0.5573855042457581, 'testing', 1), ('bokeh/bokeh', 0.5535537004470825, 'viz', 0), ('masoniteframework/masonite', 0.5500764846801758, 'web', 0), ('alirezamika/autoscraper', 0.5415842533111572, 'data', 0), ('pyodide/pyodide', 0.540057897567749, 'util', 0), ('wolever/parameterized', 0.5371958613395691, 'testing', 0), ('clips/pattern', 0.5308951735496521, 'nlp', 0), ('plotly/dash', 0.5277555584907532, 'viz', 0), ('r0x0r/pywebview', 0.5268258452415466, 'gui', 1), ('jiffyclub/snakeviz', 0.5255619287490845, 'profiling', 0), ('robotframework/robotframework', 0.5185773968696594, 'testing', 0), ('pytest-dev/pytest-testinfra', 0.5065727233886719, 'testing', 1), ('roniemartinez/dude', 0.5045518279075623, 'util', 1), ('scrapy/scrapy', 0.5043920278549194, 'data', 0), ('pallets/flask', 0.5030795931816101, 'web', 0), ('voila-dashboards/voila', 0.5014607906341553, 'jupyter', 0)]

37

5

null

16.27

167

160

120

0

130

91

130

167

348

90

2.1

54

1,212

ml

https://github.com/sanchit-gandhi/whisper-jax

[]

null

[]

null

sanchit-gandhi/whisper-jax

whisper-jax

3,813

322

39

Jupyter Notebook

null

JAX implementation of OpenAI's Whisper model for up to 70x speed-up on TPU.

sanchit-gandhi

2024-01-13

2023-03-02

47

79.913174

null

JAX implementation of OpenAI's Whisper model for up to 70x speed-up on TPU.

['deep-learning', 'jax', 'speech-recognition', 'speech-to-text', 'whisper']

2023-12-15

[('ggerganov/whisper.cpp', 0.6906029582023621, 'util', 3), ('deepmind/dm-haiku', 0.6133875846862793, 'ml-dl', 2), ('m-bain/whisperx', 0.5212621688842773, 'nlp', 3)]

4

2

null

2.44

44

17

11

1

0

44

62

90

1.4

54

284

crypto

https://github.com/ethereum/consensus-specs

[]

null

[]

null

ethereum/consensus-specs

consensus-specs

3,329

977

246

Python

null

Ethereum Proof-of-Stake Consensus Specifications

ethereum

2024-01-12

2018-09-20

279

11.90143

https://avatars.githubusercontent.com/u/6250754?v=4

Ethereum Proof-of-Stake Consensus Specifications

[]

2024-01-11

[]

148

3

null

10.83

251

107

65

0

16

251

225

90

0.9

54

1,759

data

https://github.com/rom1504/img2dataset

[]

null

[]

null

rom1504/img2dataset

img2dataset

2,953

288

29

Python

null

Easily turn large sets of image urls to an image dataset. Can download, resize and package 100M urls in 20h on one machine.

rom1504

2024-01-13

2021-08-11

128

22.916851

null

Easily turn large sets of image urls to an image dataset. Can download, resize and package 100M urls in 20h on one machine.

['big-data', 'dataset', 'deep-learning', 'download-images', 'image', 'image-dataset', 'multimodal']

2024-01-13

[('fourthbrain/fastapi-for-machine-learning-live-demo', 0.5232915878295898, 'web', 0), ('aiqc/aiqc', 0.5084776282310486, 'ml-ops', 0), ('microsoft/deepspeed', 0.5075109601020813, 'ml-dl', 1)]

32

5

null

0.54

48

29

30

0

4

35

4

48

95

90

2

54

1,359

llm

https://github.com/iryna-kondr/scikit-llm

[]

null

[]

null

iryna-kondr/scikit-llm

scikit-llm

2,820

226

36

Python

https://beastbyte.ai/

Seamlessly integrate LLMs into scikit-learn.

iryna-kondr

2024-01-12

2023-05-12

37

75.057034

null

Seamlessly integrate LLMs into scikit-learn.

['chatgpt', 'deep-learning', 'llm', 'machine-learning', 'scikit-learn', 'transformers']

2023-12-25

[('microsoft/jarvis', 0.6588683128356934, 'llm', 1), ('alpha-vllm/llama2-accessory', 0.6441587209701538, 'llm', 0), ('tigerlab-ai/tiger', 0.6261765956878662, 'llm', 1), ('koaning/scikit-lego', 0.614821195602417, 'ml', 2), ('vllm-project/vllm', 0.6003293395042419, 'llm', 1), ('microsoft/semantic-kernel', 0.5926992893218994, 'llm', 1), ('bigscience-workshop/petals', 0.5923831462860107, 'data', 2), ('pathwaycom/llm-app', 0.5918958187103271, 'llm', 2), ('microsoft/torchscale', 0.5895041823387146, 'llm', 1), ('intel/scikit-learn-intelex', 0.5876615047454834, 'perf', 2), ('h2oai/h2o-llmstudio', 0.5840808749198914, 'llm', 2), ('argilla-io/argilla', 0.5834850668907166, 'nlp', 2), ('rasbt/machine-learning-book', 0.5804186463356018, 'study', 3), ('intel/intel-extension-for-transformers', 0.5800312757492065, 'perf', 0), ('nomic-ai/gpt4all', 0.5748793482780457, 'llm', 0), ('skops-dev/skops', 0.5726227760314941, 'ml-ops', 2), ('nebuly-ai/nebullvm', 0.5629363059997559, 'perf', 1), ('deepset-ai/haystack', 0.5621213912963867, 'llm', 3), ('bobazooba/xllm', 0.5620294213294983, 'llm', 3), ('ray-project/ray-llm', 0.5598890781402588, 'llm', 2), ('automl/auto-sklearn', 0.5549347996711731, 'ml', 1), ('microsoft/onnxruntime', 0.5525389313697815, 'ml', 3), ('hegelai/prompttools', 0.5520104765892029, 'llm', 2), ('explosion/spacy-llm', 0.550988495349884, 'llm', 2), ('microsoft/promptcraft-robotics', 0.5381367206573486, 'sim', 2), ('bentoml/openllm', 0.5351253151893616, 'ml-ops', 1), ('ludwig-ai/ludwig', 0.5349180698394775, 'ml-ops', 3), ('huggingface/transformers', 0.5332709550857544, 'nlp', 2), ('mooler0410/llmspracticalguide', 0.5321641564369202, 'study', 0), ('microsoft/promptflow', 0.5263214707374573, 'llm', 2), ('young-geng/easylm', 0.5262447595596313, 'llm', 1), ('koaning/human-learn', 0.5255882143974304, 'data', 2), ('night-chen/toolqa', 0.522339940071106, 'llm', 0), ('truera/trulens', 0.5199382901191711, 'llm', 2), ('horovod/horovod', 0.5187541842460632, 'ml-ops', 2), ('skorch-dev/skorch', 0.5175820589065552, 'ml-dl', 2), ('optimalscale/lmflow', 0.5123019814491272, 'llm', 2), ('onnx/onnx', 0.5105788111686707, 'ml', 3), ('llmware-ai/llmware', 0.5102970600128174, 'llm', 2), ('embedchain/embedchain', 0.5067012310028076, 'llm', 2), ('salesforce/xgen', 0.5054061412811279, 'llm', 1), ('agenta-ai/agenta', 0.5052707195281982, 'llm', 1), ('lightning-ai/lit-gpt', 0.5048611164093018, 'llm', 0), ('paddlepaddle/paddlenlp', 0.5023376941680908, 'llm', 2), ('ageron/handson-ml2', 0.5018590688705444, 'ml', 0), ('determined-ai/determined', 0.5017955303192139, 'ml-ops', 2), ('databrickslabs/dolly', 0.5001913905143738, 'llm', 0)]

9

1

null

1.77

10

6

8

1

14

24

14

10

12

90

1.2

54

1,429

ml-dl

https://github.com/cvg/lightglue

[]

null

[]

null

cvg/lightglue

LightGlue

2,664

259

46

Python

null

LightGlue: Local Feature Matching at Light Speed (ICCV 2023)

cvg

2024-01-13

2023-06-25

31

85.150685

https://avatars.githubusercontent.com/u/840224?v=4

LightGlue: Local Feature Matching at Light Speed (ICCV 2023)

['deep-learning', 'image-matching', 'pose-estimation', 'transformers']

2023-11-21

[('facebookresearch/detr', 0.5226452350616455, 'ml-dl', 0)]

6

2

null

0.5

35

7

2

1

2

1

35

65

90

1.9

54

1,792

perf

https://github.com/airtai/faststream

[]

null

[]

null

airtai/faststream

faststream

1,435

53

12

Python

https://faststream.airt.ai/latest/

FastStream is a powerful and easy-to-use Python framework for building asynchronous services interacting with event streams such as Apache Kafka, RabbitMQ, NATS and Redis.

airtai

2024-01-13

2022-12-01

60

23.635294

https://avatars.githubusercontent.com/u/84014356?v=4

FastStream is a powerful and easy-to-use Python framework for building asynchronous services interacting with event streams such as Apache Kafka, RabbitMQ, NATS and Redis.

['asyncapi', 'asyncio', 'distributed-systems', 'fastkafka', 'faststream', 'kafka', 'nats', 'propan', 'rabbitmq', 'redis', 'stream-processing']

2024-01-13

[('pathwaycom/pathway', 0.6327610611915588, 'data', 1), ('samuelcolvin/arq', 0.6273122429847717, 'data', 2), ('python-trio/trio', 0.6224059462547302, 'perf', 0), ('magicstack/uvloop', 0.6053869128227234, 'util', 1), ('agronholm/anyio', 0.5833213329315186, 'perf', 1), ('miguelgrinberg/python-socketio', 0.5774848461151123, 'util', 1), ('pallets/quart', 0.5664022564888, 'web', 1), ('bogdanp/dramatiq', 0.5551525354385376, 'util', 1), ('aio-libs/aiohttp', 0.5545108914375305, 'web', 1), ('encode/httpx', 0.5473020672798157, 'web', 1), ('alirn76/panther', 0.5416358709335327, 'web', 0), ('sumerc/yappi', 0.5390495657920837, 'profiling', 1), ('backtick-se/cowait', 0.5363417267799377, 'util', 0), ('samuelcolvin/watchfiles', 0.5354728698730469, 'util', 1), ('encode/starlette', 0.5320852398872375, 'web', 0), ('fastai/fastcore', 0.5284400582313538, 'util', 0), ('neoteroi/blacksheep', 0.5211659073829651, 'web', 1), ('geeogi/async-python-lambda-template', 0.5201819539070129, 'template', 0), ('tornadoweb/tornado', 0.5190186500549316, 'web', 0), ('asacristani/fastapi-rocket-boilerplate', 0.5075085759162903, 'template', 0), ('fugue-project/fugue', 0.5063053369522095, 'pandas', 1), ('mher/flower', 0.5014379620552063, 'perf', 2)]

23

2

null

12.35

309

283

14

0

37

33

37

307

249

90

0.8

54

1,675

study

https://github.com/realpython/python-guide

[]

null

[]

null

realpython/python-guide

python-guide

27,160

5,988

1,384

Batchfile

https://docs.python-guide.org

Python best practices guidebook, written for humans.

realpython

2024-01-13

2011-03-15

672

40.416667

https://avatars.githubusercontent.com/u/5448020?v=4

Python best practices guidebook, written for humans.

['book', 'guide', 'kennethreitz']

2023-06-13

[('amaargiru/pyroad', 0.6154986023902893, 'study', 0), ('wesm/pydata-book', 0.5613322854042053, 'study', 0), ('eleutherai/pyfra', 0.5539833307266235, 'ml', 0), ('brandon-rhodes/python-patterns', 0.5476312637329102, 'util', 0), ('jakevdp/pythondatasciencehandbook', 0.5322774648666382, 'study', 0), ('mynameisfiber/high_performance_python_2e', 0.5209663510322571, 'study', 0), ('fchollet/deep-learning-with-python-notebooks', 0.5066047310829163, 'study', 0), ('python/cpython', 0.5037524104118347, 'util', 0), ('pytoolz/toolz', 0.5026092529296875, 'util', 0), ('ageron/handson-ml2', 0.5025880336761475, 'ml', 0)]

474

6

null

0

5

1

156

7

0

5

90

1

53

683

ml-dl

https://github.com/matterport/mask_rcnn

[]

null

[]

null

matterport/mask_rcnn

Mask_RCNN

23,803

11,620

587

Python

null

Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow

matterport

2024-01-14

2017-10-19

327

72.633391

https://avatars.githubusercontent.com/u/4206481?v=4

Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow

['instance-segmentation', 'keras', 'mask-rcnn', 'object-detection', 'tensorflow']

2019-03-31

[('open-mmlab/mmdetection', 0.5989094376564026, 'ml', 3), ('roboflow/notebooks', 0.5560668706893921, 'study', 1), ('nyandwi/modernconvnets', 0.5529733300209045, 'ml-dl', 2), ('blakeblackshear/frigate', 0.5429755449295044, 'util', 2), ('facebookresearch/segment-anything', 0.5424768328666687, 'ml-dl', 2), ('deci-ai/super-gradients', 0.5377986431121826, 'ml-dl', 1), ('facebookresearch/detectron', 0.5304756760597229, 'ml-dl', 0), ('roboflow/supervision', 0.528638482093811, 'ml', 3), ('nvlabs/gcvit', 0.5284178256988525, 'diffusion', 1), ('facebookresearch/detr', 0.5123329758644104, 'ml-dl', 0)]

47

6

null

0

49

12

76

59

0

49

51

90

1

53

643

util

https://github.com/keon/algorithms

[]

null

[]

null

keon/algorithms

algorithms

23,270

4,629

635

Python

null

Minimal examples of data structures and algorithms in Python

keon

2024-01-13

2016-11-17

375

61.935361

null

Minimal examples of data structures and algorithms in Python

['algorithm', 'algorithms', 'competitive-programming', 'data-structure', 'graph', 'search', 'sort', 'tree']

2023-04-04

[('thealgorithms/python', 0.707886815071106, 'study', 1), ('joowani/binarytree', 0.6219033002853394, 'util', 2), ('python-odin/odin', 0.6064568161964417, 'util', 0), ('pandas-dev/pandas', 0.6043705940246582, 'pandas', 0), ('pyomo/pyomo', 0.5572477579116821, 'math', 0), ('krzjoa/awesome-python-data-science', 0.5512800812721252, 'study', 0), ('gbeced/pyalgotrade', 0.5470435619354248, 'finance', 0), ('quantopian/zipline', 0.5438115000724792, 'finance', 0), ('networkx/networkx', 0.543645977973938, 'graph', 0), ('atsushisakai/pythonrobotics', 0.5353425741195679, 'sim', 1), ('sympy/sympy', 0.5286232233047485, 'math', 0), ('pytoolz/toolz', 0.520076334476471, 'util', 0), ('quantconnect/lean', 0.512477457523346, 'finance', 1), ('tiangolo/sqlmodel', 0.5121207237243652, 'data', 0), ('ranaroussi/quantstats', 0.5114973187446594, 'finance', 0), ('dagworks-inc/hamilton', 0.5108981728553772, 'ml-ops', 0), ('plotly/dash', 0.5095182657241821, 'viz', 0), ('scikit-learn/scikit-learn', 0.5060738921165466, 'ml', 0), ('rasbt/mlxtend', 0.5041128993034363, 'ml', 0), ('python/cpython', 0.5038732290267944, 'util', 0), ('scikit-mobility/scikit-mobility', 0.5026717782020569, 'gis', 0)]

198

4

null

0.12

10

1

87

10

0

10

6

90

0.6

53

105

nlp

https://github.com/rare-technologies/gensim

[]

null

[]

null

rare-technologies/gensim

gensim

14,914

4,381

433

Python

https://radimrehurek.com/gensim

Topic Modelling for Humans

rare-technologies

2024-01-14

2011-02-10

676

22.038843

null

Topic Modelling for Humans

['data-mining', 'data-science', 'document-similarity', 'fasttext', 'gensim', 'information-retrieval', 'machine-learning', 'natural-language-processing', 'neural-network', 'nlp', 'topic-modeling', 'word-embeddings', 'word-similarity', 'word2vec']

2023-10-01

[('ddangelov/top2vec', 0.59908527135849, 'nlp', 2), ('maartengr/bertopic', 0.5905485153198242, 'nlp', 3), ('brettkromkamp/topic-db', 0.539949893951416, 'data', 0), ('ddbourgin/numpy-ml', 0.5375690460205078, 'ml', 3), ('sebischair/lbl2vec', 0.5351875424385071, 'nlp', 4), ('sloria/textblob', 0.5176156759262085, 'nlp', 2), ('milvus-io/bootcamp', 0.5120472311973572, 'data', 1)]

449

6

null

1.42

20

3

157

4

1

6

1

20

25

90

1.2

53

1,884

util

https://github.com/ninja-build/ninja

['build']

Ninja is a small build system with a focus on speed.

[]

null

ninja-build/ninja

ninja

10,184

1,544

264

C++

https://ninja-build.org/

a small build system with a focus on speed

ninja-build

2024-01-14

2011-02-06

677

15.03649

https://avatars.githubusercontent.com/u/11653218?v=4

a small build system with a focus on speed

[]

['build']

2024-01-02

[('scikit-build/scikit-build', 0.562438428401947, 'ml', 0)]

285

4

null

0.73

76

42

157

0

2

76

107

90

1.4

53

133

ml

https://github.com/epistasislab/tpot

[]

null

[]

null

epistasislab/tpot

tpot

9,381

1,552

290

Python

http://epistasislab.github.io/tpot/

A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

epistasislab

2024-01-13

2015-11-03

430

21.816279

https://avatars.githubusercontent.com/u/20861190?v=4

A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

['adsp', 'ag066833', 'aiml', 'alzheimer', 'alzheimers', 'automated-machine-learning', 'automation', 'automl', 'data-science', 'feature-engineering', 'gradient-boosting', 'hyperparameter-optimization', 'machine-learning', 'model-selection', 'nia', 'parameter-tuning', 'random-forest', 'scikit-learn', 'u01ag066833']

2023-12-08

[('automl/auto-sklearn', 0.6574358940124512, 'ml', 4), ('featurelabs/featuretools', 0.6507097482681274, 'ml', 6), ('microsoft/nni', 0.6485167741775513, 'ml', 6), ('google/pyglove', 0.6232022643089294, 'util', 2), ('scikit-learn/scikit-learn', 0.6184797286987305, 'ml', 2), ('mljar/mljar-supervised', 0.6145864129066467, 'ml', 8), ('google/vizier', 0.6137571930885315, 'ml', 2), ('microsoft/flaml', 0.6104899048805237, 'ml', 7), ('nccr-itmo/fedot', 0.6070546507835388, 'ml-ops', 6), ('gradio-app/gradio', 0.5918328166007996, 'viz', 2), ('rasbt/mlxtend', 0.5866554379463196, 'ml', 2), ('determined-ai/determined', 0.5670955777168274, 'ml-ops', 3), ('districtdatalabs/yellowbrick', 0.5539801120758057, 'ml', 3), ('ray-project/ray', 0.5462473034858704, 'ml-ops', 5), ('wandb/client', 0.5462185144424438, 'ml', 3), ('scikit-learn-contrib/imbalanced-learn', 0.545037567615509, 'ml', 2), ('merantix-momentum/squirrel-core', 0.5355274081230164, 'ml', 2), ('selfexplainml/piml-toolbox', 0.5343623161315918, 'ml-interpretability', 0), ('pycaret/pycaret', 0.5342784523963928, 'ml', 2), ('awslabs/autogluon', 0.5319231748580933, 'ml', 6), ('scikit-optimize/scikit-optimize', 0.5264012217521667, 'ml', 3), ('kubeflow/fairing', 0.5261349081993103, 'ml-ops', 0), ('ml-tooling/opyrator', 0.5252538323402405, 'viz', 1), ('ageron/handson-ml2', 0.5202245712280273, 'ml', 0), ('dagworks-inc/hamilton', 0.5198063850402832, 'ml-ops', 3), ('catboost/catboost', 0.515169084072113, 'ml', 3), ('polyaxon/polyaxon', 0.5143507122993469, 'ml-ops', 3), ('keras-team/autokeras', 0.5138368010520935, 'ml-dl', 3), ('koaning/scikit-lego', 0.5125021934509277, 'ml', 2), ('rasbt/machine-learning-book', 0.5111925601959229, 'study', 2), ('online-ml/river', 0.5093849897384644, 'ml', 2), ('karpathy/micrograd', 0.5062547922134399, 'study', 0), ('huggingface/datasets', 0.50594562292099, 'nlp', 1), ('rafiqhasan/auto-tensorflow', 0.5045480132102966, 'ml-dl', 2), ('firmai/atspy', 0.5008826851844788, 'time-series', 0)]

118

8

null

0.4

14

6

100

1

2

4

2

14

16

90

1.1

53

397

web

https://github.com/falconry/falcon

[]

null

[]

null

falconry/falcon

falcon

9,306

926

262

Python

https://falcon.readthedocs.io/en/stable/

The no-magic web data plane API and microservices framework for Python developers, with a focus on reliability, correctness, and performance at scale.

falconry

2024-01-12

2012-12-06

581

15.997544

https://avatars.githubusercontent.com/u/11353642?v=4

The no-magic web data plane API and microservices framework for Python developers, with a focus on reliability, correctness, and performance at scale.

['api', 'api-rest', 'asgi', 'framework', 'http', 'microservices', 'rest', 'web', 'wsgi']

2023-12-26

[('pallets/flask', 0.7083405256271362, 'web', 1), ('neoteroi/blacksheep', 0.6875892877578735, 'web', 4), ('pallets/quart', 0.6842796206474304, 'web', 1), ('starlite-api/starlite', 0.6774393916130066, 'web', 3), ('bottlepy/bottle', 0.677134096622467, 'web', 2), ('encode/uvicorn', 0.6588360667228699, 'web', 2), ('klen/muffin', 0.6537138819694519, 'web', 1), ('python-restx/flask-restx', 0.6462195515632629, 'web', 2), ('masoniteframework/masonite', 0.6416914463043213, 'web', 2), ('pallets/werkzeug', 0.630772590637207, 'web', 2), ('simple-salesforce/simple-salesforce', 0.6300815939903259, 'data', 1), ('hugapi/hug', 0.6300604343414307, 'util', 1), ('requests/toolbelt', 0.6299983263015747, 'util', 1), ('pylons/pyramid', 0.6222757697105408, 'web', 1), ('webpy/webpy', 0.6171799302101135, 'web', 0), ('encode/httpx', 0.6106772422790527, 'web', 1), ('vitalik/django-ninja', 0.6103278994560242, 'web', 0), ('tiangolo/fastapi', 0.608084499835968, 'web', 4), ('cherrypy/cherrypy', 0.6051623821258545, 'web', 1), ('reflex-dev/reflex', 0.5998751521110535, 'web', 1), ('scrapy/scrapy', 0.5992222428321838, 'data', 1), ('tiangolo/sqlmodel', 0.5907256007194519, 'data', 0), ('eleutherai/pyfra', 0.5904573202133179, 'ml', 0), ('nficano/python-lambda', 0.5897996425628662, 'util', 1), ('jordaneremieff/mangum', 0.5848598480224609, 'web', 1), ('aws/chalice', 0.5833958387374878, 'web', 0), ('alirn76/panther', 0.5779109001159668, 'web', 1), ('pyeve/eve', 0.5698334574699402, 'web', 1), ('ml-tooling/opyrator', 0.5693379044532776, 'viz', 1), ('willmcgugan/textual', 0.562833845615387, 'term', 1), ('psf/requests', 0.5613847970962524, 'web', 1), ('pylons/waitress', 0.5612348318099976, 'web', 0), ('timofurrer/awesome-asyncio', 0.5593904852867126, 'study', 0), ('backtick-se/cowait', 0.5538949370384216, 'util', 0), ('taverntesting/tavern', 0.5523936152458191, 'testing', 1), ('plotly/dash', 0.5521128177642822, 'viz', 0), ('asacristani/fastapi-rocket-boilerplate', 0.5512214303016663, 'template', 0), ('flet-dev/flet', 0.5503961443901062, 'web', 1), ('tiangolo/full-stack-fastapi-postgresql', 0.5487000942230225, 'template', 0), ('nasdaq/data-link-python', 0.5472946763038635, 'finance', 0), ('kubeflow/fairing', 0.5438461303710938, 'ml-ops', 0), ('fastai/fastcore', 0.5430771708488464, 'util', 0), ('holoviz/panel', 0.5421604514122009, 'viz', 0), ('ethereum/web3.py', 0.540778636932373, 'crypto', 0), ('clips/pattern', 0.5375832915306091, 'nlp', 0), ('ets-labs/python-dependency-injector', 0.5372539758682251, 'util', 0), ('amzn/ion-python', 0.5367324352264404, 'data', 0), ('roniemartinez/dude', 0.5347031354904175, 'util', 1), ('huge-success/sanic', 0.5344210267066956, 'web', 3), ('benoitc/gunicorn', 0.5321671366691589, 'web', 2), ('python-odin/odin', 0.5320534706115723, 'util', 0), ('merantix-momentum/squirrel-core', 0.5313084721565247, 'ml', 0), ('ibis-project/ibis', 0.5278680324554443, 'data', 0), ('locustio/locust', 0.5264105200767517, 'testing', 1), ('pyinfra-dev/pyinfra', 0.5231207609176636, 'util', 0), ('openai/openai-python', 0.5228433609008789, 'util', 0), ('ajndkr/lanarky', 0.5218005180358887, 'llm', 1), ('dylanhogg/awesome-python', 0.5216991901397705, 'study', 0), ('simonw/datasette', 0.5216467380523682, 'data', 1), ('pytoolz/toolz', 0.5214901566505432, 'util', 0), ('lk-geimfari/mimesis', 0.5205872654914856, 'data', 0), ('geopandas/geopandas', 0.5166769027709961, 'gis', 0), ('alirezamika/autoscraper', 0.513289749622345, 'data', 0), ('aio-libs/aiohttp', 0.512401819229126, 'web', 1), ('pytables/pytables', 0.5114437937736511, 'data', 0), ('pynamodb/pynamodb', 0.5108199119567871, 'data', 0), ('sqlalchemy/sqlalchemy', 0.509283185005188, 'data', 0), ('radiantearth/radiant-mlhub', 0.5079211592674255, 'gis', 0), ('snyk-labs/pysnyk', 0.5076401829719543, 'security', 1), ('1200wd/bitcoinlib', 0.5075222849845886, 'crypto', 0), ('amaargiru/pyroad', 0.5072835087776184, 'study', 0), ('micropython/micropython', 0.507040798664093, 'util', 0), ('eventual-inc/daft', 0.5012557506561279, 'pandas', 0), ('shishirpatil/gorilla', 0.500187873840332, 'llm', 1)]

201

4

null

0.42

43

24

135

1

6

7

6

43

59

90

1.4

53

293

util

https://github.com/paramiko/paramiko

[]

null

[]

null

paramiko/paramiko

paramiko

8,659

2,010

316

Python

http://paramiko.org

The leading native Python SSHv2 protocol library.

paramiko

2024-01-14

2009-02-02

782

11.070868

https://avatars.githubusercontent.com/u/1108455?v=4

The leading native Python SSHv2 protocol library.

[]

2023-12-18

[('pypy/pypy', 0.6160950064659119, 'util', 0), ('pyston/pyston', 0.5798661708831787, 'util', 0), ('secdev/scapy', 0.5442431569099426, 'util', 0), ('legrandin/pycryptodome', 0.5410947203636169, 'util', 0), ('pytoolz/toolz', 0.5407304763793945, 'util', 0), ('1200wd/bitcoinlib', 0.5394938588142395, 'crypto', 0), ('ethereum/py-evm', 0.5358531475067139, 'crypto', 0), ('urwid/urwid', 0.5337045192718506, 'term', 0), ('cherrypy/cherrypy', 0.5295555591583252, 'web', 0), ('oracle/graalpython', 0.5263757109642029, 'util', 0), ('encode/httpx', 0.5251051187515259, 'web', 0), ('websocket-client/websocket-client', 0.5153641700744629, 'web', 0), ('pyca/cryptography', 0.5152232646942139, 'util', 0), ('python/cpython', 0.5128664374351501, 'util', 0), ('pyca/pynacl', 0.5029951930046082, 'util', 0), ('libtcod/python-tcod', 0.502030611038208, 'gamedev', 0), ('primal100/pybitcointools', 0.5015236139297485, 'crypto', 0)]

187

5

null

2.58

65

15

182

1

0

12

65

111

90

1.7

53

1,433

ml-dl

https://github.com/nvidia/apex

[]

null

[]

null

nvidia/apex

apex

7,797

1,306

102

Python

null

A PyTorch Extension: Tools for easy mixed precision and distributed training in Pytorch

nvidia

2024-01-14

2018-04-23

301

25.891366

https://avatars.githubusercontent.com/u/1728152?v=4

A PyTorch Extension: Tools for easy mixed precision and distributed training in Pytorch

[]

2024-01-12

[('pytorch/ignite', 0.76711106300354, 'ml-dl', 0), ('huggingface/accelerate', 0.7648141980171204, 'ml', 0), ('intel/intel-extension-for-pytorch', 0.7110769152641296, 'perf', 0), ('skorch-dev/skorch', 0.6882312893867493, 'ml-dl', 0), ('pytorch/data', 0.6665452122688293, 'data', 0), ('laekov/fastmoe', 0.6603500247001648, 'ml', 0), ('mrdbourke/pytorch-deep-learning', 0.6514618396759033, 'study', 0), ('karpathy/micrograd', 0.6441670060157776, 'study', 0), ('rasbt/machine-learning-book', 0.6338503956794739, 'study', 0), ('arogozhnikov/einops', 0.6182481646537781, 'ml-dl', 0), ('denys88/rl_games', 0.6122349500656128, 'ml-rl', 0), ('karpathy/mingpt', 0.6042015552520752, 'llm', 0), ('rentruewang/koila', 0.6033901572227478, 'ml', 0), ('nicolas-chaulet/torch-points3d', 0.5915487408638, 'ml', 0), ('horovod/horovod', 0.5866835117340088, 'ml-ops', 0), ('allenai/allennlp', 0.5706870555877686, 'nlp', 0), ('pyg-team/pytorch_geometric', 0.5672152042388916, 'ml-dl', 0), ('pytorch/botorch', 0.5640817880630493, 'ml-dl', 0), ('hysts/pytorch_image_classification', 0.5612041354179382, 'ml-dl', 0), ('determined-ai/determined', 0.5580594539642334, 'ml-ops', 0), ('pytorch/captum', 0.5534337759017944, 'ml-interpretability', 0), ('ashleve/lightning-hydra-template', 0.553119957447052, 'util', 0), ('davidmrau/mixture-of-experts', 0.5525276064872742, 'ml', 0), ('pytorch/rl', 0.552091121673584, 'ml-rl', 0), ('huggingface/transformers', 0.5461992621421814, 'nlp', 0), ('kshitij12345/torchnnprofiler', 0.5381832718849182, 'profiling', 0), ('blackhc/toma', 0.5342817902565002, 'ml-dl', 0), ('pytorch-labs/gpt-fast', 0.5303529500961304, 'llm', 0), ('xl0/lovely-tensors', 0.5290429592132568, 'ml-dl', 0), ('facebookresearch/pytorch3d', 0.5290184020996094, 'ml-dl', 0), ('intellabs/bayesian-torch', 0.5274893045425415, 'ml', 0), ('thu-ml/tianshou', 0.5245383381843567, 'ml-rl', 0), ('timdettmers/bitsandbytes', 0.5227283239364624, 'util', 0), ('faster-cpython/tools', 0.5224118828773499, 'perf', 0), ('salesforce/blip', 0.5196071267127991, 'diffusion', 0), ('mcahny/deep-video-inpainting', 0.514928936958313, 'ml-dl', 0), ('huggingface/optimum', 0.5144795179367065, 'ml', 0), ('huggingface/peft', 0.5134326219558716, 'llm', 0), ('uber/petastorm', 0.5052030086517334, 'data', 0), ('dask/dask-ml', 0.5042513608932495, 'ml', 0), ('paddlepaddle/paddle', 0.5022732019424438, 'ml-dl', 0), ('hazyresearch/hgcn', 0.502190113067627, 'ml', 0)]

125

2

null

1.65

70

35

70

0

1

70

87

90

1.2

53

388

data

https://github.com/yzhao062/pyod

[]

null

[]

null

yzhao062/pyod

pyod

7,738

1,307

148

Python

http://pyod.readthedocs.io

A Comprehensive and Scalable Python Library for Outlier Detection (Anomaly Detection)

yzhao062

2024-01-13

2017-10-03

330

23.448485

null

A Comprehensive and Scalable Python Library for Outlier Detection (Anomaly Detection)

['anomaly', 'anomaly-detection', 'autoencoder', 'data-analysis', 'data-mining', 'data-science', 'deep-learning', 'fraud-detection', 'machine-learning', 'neural-networks', 'novelty-detection', 'out-of-distribution-detection', 'outlier-detection', 'outlier-ensembles', 'outliers', 'unsupervised-learning']

2023-12-16

[('pycaret/pycaret', 0.7633078694343567, 'ml', 3), ('unit8co/darts', 0.7557379603385925, 'time-series', 4), ('aistream-peelout/flow-forecast', 0.6631090044975281, 'time-series', 2), ('tdameritrade/stumpy', 0.6203436255455017, 'time-series', 2), ('rasbt/mlxtend', 0.6038527488708496, 'ml', 4), ('scikit-learn-contrib/imbalanced-learn', 0.589371383190155, 'ml', 3), ('salesforce/merlion', 0.5439088940620422, 'time-series', 2), ('featurelabs/featuretools', 0.5403005480766296, 'ml', 2), ('salesforce/logai', 0.5268727540969849, 'util', 2), ('mdbloice/augmentor', 0.5144423842430115, 'ml', 3), ('scikit-learn/scikit-learn', 0.5111293196678162, 'ml', 3), ('alkaline-ml/pmdarima', 0.5062800049781799, 'time-series', 1), ('jeshraghian/snntorch', 0.5056750178337097, 'ml-dl', 2)]

50

5

null

0.83

21

9

76

1

4

6

4

21

25

90

1.2

53

1,257

llm

https://github.com/openlm-research/open_llama

['llama', 'language-model']

OpenLLaMA: An Open Reproduction of LLaMA

['2302.13971']

[]

null

openlm-research/open_llama

open_llama

7,006

362

115

null

OpenLLaMA, a permissively licensed open source reproduction of Meta AI’s LLaMA 7B trained on the RedPajama dataset

openlm-research

2024-01-13

2023-04-28

39

177.046931

https://avatars.githubusercontent.com/u/132110378?v=4

OpenLLaMA, a permissively licensed open source reproduction of Meta AI’s LLaMA 7B trained on the RedPajama dataset

[]

['language-model', 'llama']

2023-07-16

[('microsoft/llama-2-onnx', 0.6107590794563293, 'llm', 2), ('jzhang38/tinyllama', 0.5819482207298279, 'llm', 2), ('facebookresearch/llama', 0.5816770195960999, 'llm', 2), ('togethercomputer/redpajama-data', 0.5621833801269531, 'llm', 0), ('lm-sys/fastchat', 0.5599814653396606, 'llm', 1), ('karpathy/llama2.c', 0.5405749678611755, 'llm', 2), ('cg123/mergekit', 0.537260890007019, 'llm', 1), ('facebookresearch/codellama', 0.5370882153511047, 'llm', 2), ('facebookresearch/llama-recipes', 0.536719799041748, 'llm', 2), ('yueyu1030/attrprompt', 0.5280580520629883, 'llm', 0), ('bobazooba/xllm', 0.5272755026817322, 'llm', 1), ('lightning-ai/lit-llama', 0.5196517109870911, 'llm', 2), ('bigscience-workshop/petals', 0.5177329778671265, 'data', 1), ('lupantech/chameleon-llm', 0.5159003138542175, 'llm', 1), ('mshumer/gpt-llm-trainer', 0.5152719616889954, 'llm', 0), ('eleutherai/the-pile', 0.5138996839523315, 'data', 0), ('juncongmoo/pyllama', 0.5135765671730042, 'llm', 0), ('google-research/language', 0.5121092796325684, 'nlp', 0), ('tairov/llama2.mojo', 0.5117022395133972, 'llm', 1), ('tigerlab-ai/tiger', 0.5050448179244995, 'llm', 0), ('run-llama/llama-lab', 0.5049968957901001, 'llm', 2), ('lucidrains/toolformer-pytorch', 0.5018919110298157, 'llm', 1), ('aiwaves-cn/agents', 0.5005034804344177, 'nlp', 1)]

3

null

0.35

8

3

9

6

0

8

3

90

0.4

53

69

gamedev

https://github.com/pygame/pygame

[]

null

[]

1

null

pygame/pygame

pygame

6,667

2,977

160

C

https://www.pygame.org

🐍🎮 pygame (the library) is a Free and Open Source python programming language library for making multimedia applications like games built on top of the excellent SDL library. C, Python, Native, OpenGL.

pygame

2024-01-14

2017-03-26

357

18.660136

https://avatars.githubusercontent.com/u/20628127?v=4

🐍🎮 pygame (the library) is a Free and Open Source python programming language library for making multimedia applications like games built on top of the excellent SDL library. C, Python, Native, OpenGL.

['game-dev', 'game-development', 'gamedev', 'pygame', 'sdl', 'sdl2']

2023-12-30

[('pyglet/pyglet', 0.717469334602356, 'gamedev', 1), ('renpy/pygame_sdl2', 0.7130681872367859, 'gamedev', 2), ('lordmauve/pgzero', 0.6985493302345276, 'gamedev', 1), ('pygamelib/pygamelib', 0.6512402892112732, 'gamedev', 2), ('pythonarcade/arcade', 0.6259638071060181, 'gamedev', 0), ('panda3d/panda3d', 0.609826922416687, 'gamedev', 2), ('kitao/pyxel', 0.5883877873420715, 'gamedev', 2), ('pokepetter/ursina', 0.5800055861473083, 'gamedev', 1), ('viblo/pymunk', 0.5696349740028381, 'sim', 1), ('renpy/renpy', 0.5524816513061523, 'viz', 0), ('pypy/pypy', 0.5523542165756226, 'util', 0), ('pytoolz/toolz', 0.5287861824035645, 'util', 0), ('hoffstadt/dearpygui', 0.5225834846496582, 'gui', 0), ('urwid/urwid', 0.5163580775260925, 'term', 0), ('jquast/blessed', 0.504092812538147, 'term', 0)]

315

0

null

9.33

125

37

83

0

11

13

11

125

134

90

1.1

53

74

gis

https://github.com/python-visualization/folium

[]

null

[]

null

python-visualization/folium

folium

6,539

2,245

167

Python

https://python-visualization.github.io/folium/

Python Data. Leaflet.js Maps.

python-visualization

2024-01-13

2013-05-09

559

11.682746

https://avatars.githubusercontent.com/u/9969242?v=4

Python Data. Leaflet.js Maps.

['data-science', 'data-visualization', 'javascript', 'maps']

2024-01-02

[('jupyter-widgets/ipyleaflet', 0.6334434151649475, 'gis', 0), ('bokeh/bokeh', 0.5900196433067322, 'viz', 1), ('plotly/dash', 0.5898042321205139, 'viz', 2), ('giswqs/mapwidget', 0.5697619915008545, 'gis', 0), ('giswqs/geemap', 0.5445337295532227, 'gis', 1), ('raphaelquast/eomaps', 0.5424359440803528, 'gis', 0), ('opengeos/leafmap', 0.5398542284965515, 'gis', 1), ('holoviz/panel', 0.5396947860717773, 'viz', 0), ('plotly/plotly.py', 0.5229291319847107, 'viz', 0), ('man-group/dtale', 0.5144950747489929, 'viz', 2)]

159

5

null

2

57

41

130

0

2

57

114

90

2

53

793

web

https://github.com/pallets/werkzeug

[]

null

[]

null

pallets/werkzeug

werkzeug

6,480

1,729

221

Python

https://werkzeug.palletsprojects.com

The comprehensive WSGI web application library.

pallets

2024-01-13

2010-10-18

693

9.348722

https://avatars.githubusercontent.com/u/16748505?v=4

The comprehensive WSGI web application library.

['http', 'pallets', 'werkzeug', 'wsgi']

2024-01-01

[('pallets/flask', 0.7842201590538025, 'web', 3), ('pylons/pyramid', 0.7471210360527039, 'web', 1), ('bottlepy/bottle', 0.6876417994499207, 'web', 1), ('benoitc/gunicorn', 0.6659462451934814, 'web', 2), ('masoniteframework/masonite', 0.6412118673324585, 'web', 0), ('falconry/falcon', 0.630772590637207, 'web', 2), ('pylons/waitress', 0.6237661838531494, 'web', 0), ('pylons/webob', 0.6051927804946899, 'web', 1), ('neoteroi/blacksheep', 0.5996673703193665, 'web', 1), ('webpy/webpy', 0.5957249999046326, 'web', 0), ('cherrypy/cherrypy', 0.5869470834732056, 'web', 1), ('encode/uvicorn', 0.5832026600837708, 'web', 1), ('klen/muffin', 0.5703849196434021, 'web', 0), ('encode/httpx', 0.5651618838310242, 'web', 1), ('scrapy/scrapy', 0.5650268197059631, 'data', 0), ('reflex-dev/reflex', 0.5643238425254822, 'web', 0), ('requests/toolbelt', 0.5638414025306702, 'util', 1), ('psf/requests', 0.559667706489563, 'web', 1), ('pallets/quart', 0.5403130054473877, 'web', 0), ('python-restx/flask-restx', 0.5365567803382874, 'web', 0), ('willmcgugan/textual', 0.5303859114646912, 'term', 0), ('hugapi/hug', 0.5272501111030579, 'util', 1), ('eleutherai/pyfra', 0.523544430732727, 'ml', 0), ('emmett-framework/emmett', 0.5205287337303162, 'web', 0), ('tiangolo/full-stack-fastapi-postgresql', 0.520187497138977, 'template', 0), ('mlc-ai/web-llm', 0.5196402668952942, 'llm', 0), ('roniemartinez/dude', 0.5181063413619995, 'util', 0), ('flet-dev/flet', 0.5143693089485168, 'web', 0), ('starlite-api/starlite', 0.5068367123603821, 'web', 0), ('aminalaee/sqladmin', 0.5044029355049133, 'data', 1), ('encode/starlette', 0.5027870535850525, 'web', 1), ('clips/pattern', 0.5018793344497681, 'nlp', 0)]

486

5

null

4.12

47

33

161

0

12

7

12

47

41

90

0.9

53

1,640

llm

https://github.com/nat/openplayground

['language-model', 'local']

null

[]

null

nat/openplayground

openplayground

5,904

441

58

TypeScript

null

An LLM playground you can run on your laptop

nat

2024-01-14

2023-02-26

48

122.272189

null

An LLM playground you can run on your laptop

[]

['language-model', 'local']

2023-06-05

[('eugeneyan/open-llms', 0.6209505796432495, 'study', 0), ('alphasecio/langchain-examples', 0.6207661628723145, 'llm', 0), ('hwchase17/langchain', 0.607382595539093, 'llm', 1), ('young-geng/easylm', 0.593249499797821, 'llm', 1), ('thudm/chatglm2-6b', 0.5894226431846619, 'llm', 0), ('mlc-ai/web-llm', 0.589094340801239, 'llm', 1), ('nomic-ai/gpt4all', 0.5870195627212524, 'llm', 1), ('langchain-ai/langgraph', 0.5708506107330322, 'llm', 0), ('alpha-vllm/llama2-accessory', 0.5689014792442322, 'llm', 0), ('tigerlab-ai/tiger', 0.5651535987854004, 'llm', 0), ('salesforce/xgen', 0.5570892095565796, 'llm', 1), ('hiyouga/llama-factory', 0.5530926585197449, 'llm', 1), ('hiyouga/llama-efficient-tuning', 0.5530924797058105, 'llm', 1), ('agenta-ai/agenta', 0.5450541973114014, 'llm', 0), ('salesforce/codet5', 0.5432443022727966, 'nlp', 1), ('microsoft/llama-2-onnx', 0.5403831005096436, 'llm', 1), ('intel/intel-extension-for-transformers', 0.5346694588661194, 'perf', 0), ('microsoft/torchscale', 0.5345559120178223, 'llm', 0), ('conceptofmind/toolformer', 0.5319477915763855, 'llm', 1), ('langchain-ai/langsmith-cookbook', 0.5300737619400024, 'llm', 1), ('mooler0410/llmspracticalguide', 0.5199169516563416, 'study', 0), ('nvidia/nemo-guardrails', 0.5180691480636597, 'llm', 1), ('ctlllll/llm-toolmaker', 0.5115349292755127, 'llm', 1), ('sjtu-ipads/powerinfer', 0.5090302228927612, 'llm', 0), ('hannibal046/awesome-llm', 0.5065643787384033, 'study', 1), ('deep-diver/pingpong', 0.5059070587158203, 'llm', 0), ('prefecthq/langchain-prefect', 0.5041869282722473, 'llm', 0), ('mlc-ai/mlc-llm', 0.5039643049240112, 'llm', 1), ('cg123/mergekit', 0.5010144710540771, 'llm', 0)]

16

3

null

0.67

11

2

11

7

0

11

5

90

0.5

53

182

security

https://github.com/pycqa/bandit

['code-quality']

null

[]

null

pycqa/bandit

bandit

5,722

569

66

Python

https://bandit.readthedocs.io

Bandit is a tool designed to find common security issues in Python code.

pycqa

2024-01-13

2018-04-26

300

19.028029

https://avatars.githubusercontent.com/u/8749848?v=4

Bandit is a tool designed to find common security issues in Python code.

['bandit', 'linter', 'security', 'security-scanner', 'security-tools', 'static-code-analysis']

['bandit', 'code-quality', 'linter', 'security', 'security-scanner', 'security-tools', 'static-code-analysis']

2024-01-13

[('aswinnnn/pyscan', 0.5267046093940735, 'security', 3), ('nedbat/coveragepy', 0.5142317414283752, 'testing', 0)]

175

5

null

0.87

48

29

70

0

2

7

2

48

49

90

1

53

1,354

util

https://github.com/icloud-photos-downloader/icloud_photos_downloader

['photos-export', 'library-photos']

null

[]

null

icloud-photos-downloader/icloud_photos_downloader

icloud_photos_downloader

5,476

506

100

Python

null

A command-line tool to download photos from iCloud

icloud-photos-downloader

2024-01-14

2016-05-13

402

13.602555

https://avatars.githubusercontent.com/u/73247967?v=4

A command-line tool to download photos from iCloud

[]

['library-photos', 'photos-export']

2024-01-05

[]

36

2

null

2.23

97

57

93

0

28

4

28

96

244

90

2.5

53

510

util

https://github.com/agronholm/apscheduler

[]

null

[]

null

agronholm/apscheduler

apscheduler

5,463

698

128

Python

null

Task scheduling library for Python

agronholm

2024-01-14

2016-03-27

409

13.347644

null

Task scheduling library for Python

[]

2024-01-11

[('dbader/schedule', 0.7123571634292603, 'util', 0), ('dask/dask', 0.6700900197029114, 'perf', 0), ('pyinvoke/invoke', 0.6340285539627075, 'util', 0), ('pypy/pypy', 0.6140989065170288, 'util', 0), ('pytoolz/toolz', 0.6112861037254333, 'util', 0), ('bogdanp/dramatiq', 0.6053295135498047, 'util', 0), ('dask/distributed', 0.5948215126991272, 'perf', 0), ('python/cpython', 0.5778864622116089, 'util', 0), ('joblib/loky', 0.5760906934738159, 'perf', 0), ('eleutherai/pyfra', 0.5697214603424072, 'ml', 0), ('faster-cpython/ideas', 0.5676429867744446, 'perf', 0), ('erotemic/ubelt', 0.5611792802810669, 'util', 0), ('pyston/pyston', 0.5583381652832031, 'util', 0), ('pympler/pympler', 0.5432737469673157, 'perf', 0), ('joblib/joblib', 0.5400955080986023, 'util', 0), ('micropython/micropython', 0.5366904139518738, 'util', 0), ('sumerc/yappi', 0.5361764430999756, 'profiling', 0), ('ipython/ipyparallel', 0.529596745967865, 'perf', 0), ('fastai/fastcore', 0.5230339765548706, 'util', 0), ('kubeflow/fairing', 0.5141321420669556, 'ml-ops', 0), ('requests/toolbelt', 0.5136269330978394, 'util', 0), ('samuelcolvin/arq', 0.5115315914154053, 'data', 0), ('python-trio/trio', 0.5111809968948364, 'perf', 0), ('firmai/atspy', 0.5056720972061157, 'time-series', 0), ('faster-cpython/tools', 0.5040667057037354, 'perf', 0), ('artemyk/dynpy', 0.5037860870361328, 'sim', 0), ('merantix-momentum/squirrel-core', 0.5034119486808777, 'ml', 0), ('backtick-se/cowait', 0.502835750579834, 'util', 0), ('urwid/urwid', 0.501419186592102, 'term', 0)]

44

3

null

2.81

48

27

95

0

2

8

2

48

184

90

3.8

53

561

gis

https://github.com/gboeing/osmnx

[]

null

[]

null

gboeing/osmnx

osmnx

4,514

805

116

Python

https://osmnx.readthedocs.io

OSMnx is a Python package to easily download, model, analyze, and visualize street networks and other geospatial features from OpenStreetMap.

gboeing

2024-01-13

2016-07-24

392

11.506919

null

OSMnx is a Python package to easily download, model, analyze, and visualize street networks and other geospatial features from OpenStreetMap.

['geography', 'geospatial', 'gis', 'mapping', 'networks', 'networkx', 'openstreetmap', 'osm', 'osmnx', 'overpass-api', 'routing', 'spatial', 'spatial-analysis', 'spatial-data', 'street-networks', 'transport', 'transportation', 'urban', 'urban-planning']

2024-01-12

[('gboeing/osmnx-examples', 0.7930247187614441, 'gis', 5), ('marceloprates/prettymaps', 0.6797459125518799, 'viz', 1), ('gboeing/street-network-models', 0.5225948691368103, 'sim', 0), ('westhealth/pyvis', 0.5170513987541199, 'graph', 1)]

83

3

null

11.06

42

38

91

0

8

42

68

90

1.6

53

727

ml-dl

https://github.com/pytorch/ignite

[]

null

[]

1

null

pytorch/ignite

ignite

4,411

611

60

Python

https://pytorch-ignite.ai

High-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently.

pytorch

2024-01-13

2017-11-23

322

13.668437

https://avatars.githubusercontent.com/u/21003710?v=4

High-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently.

['deep-learning', 'machine-learning', 'metrics', 'neural-network', 'pytorch']

2024-01-11

[('skorch-dev/skorch', 0.8268391489982605, 'ml-dl', 2), ('mrdbourke/pytorch-deep-learning', 0.7811650037765503, 'study', 3), ('intel/intel-extension-for-pytorch', 0.7741976380348206, 'perf', 4), ('nvidia/apex', 0.76711106300354, 'ml-dl', 0), ('pyg-team/pytorch_geometric', 0.7287918925285339, 'ml-dl', 2), ('rasbt/machine-learning-book', 0.7284553050994873, 'study', 3), ('karpathy/micrograd', 0.7160765528678894, 'study', 0), ('pytorch/captum', 0.6821672916412354, 'ml-interpretability', 0), ('denys88/rl_games', 0.6810092926025391, 'ml-rl', 2), ('pytorch/rl', 0.6654600501060486, 'ml-rl', 2), ('allenai/allennlp', 0.6625421047210693, 'nlp', 2), ('huggingface/accelerate', 0.6613282561302185, 'ml', 0), ('intellabs/bayesian-torch', 0.6580493450164795, 'ml', 2), ('pytorch/data', 0.655742347240448, 'data', 0), ('ashleve/lightning-hydra-template', 0.6497684717178345, 'util', 2), ('xl0/lovely-tensors', 0.6465728282928467, 'ml-dl', 2), ('arogozhnikov/einops', 0.6346755027770996, 'ml-dl', 2), ('huggingface/transformers', 0.6338894367218018, 'nlp', 3), ('lightly-ai/lightly', 0.6327634453773499, 'ml', 3), ('laekov/fastmoe', 0.6223480701446533, 'ml', 0), ('rentruewang/koila', 0.6201809644699097, 'ml', 4), ('lucidrains/imagen-pytorch', 0.6169648766517639, 'ml-dl', 1), ('nicolas-chaulet/torch-points3d', 0.6167212128639221, 'ml', 0), ('ageron/handson-ml2', 0.6152977347373962, 'ml', 0), ('hysts/pytorch_image_classification', 0.615060031414032, 'ml-dl', 1), ('facebookresearch/pytorch3d', 0.6142131686210632, 'ml-dl', 0), ('neuralmagic/sparseml', 0.6128144860267639, 'ml-dl', 1), ('thu-ml/tianshou', 0.6126653552055359, 'ml-rl', 1), ('determined-ai/determined', 0.6104621291160583, 'ml-ops', 3), ('horovod/horovod', 0.6100185513496399, 'ml-ops', 3), ('tensorlayer/tensorlayer', 0.6070582866668701, 'ml-rl', 2), ('oml-team/open-metric-learning', 0.6061093807220459, 'ml', 2), ('kshitij12345/torchnnprofiler', 0.6059595346450806, 'profiling', 0), ('ggerganov/ggml', 0.6042031645774841, 'ml', 1), ('keras-team/keras', 0.5964016318321228, 'ml-dl', 3), ('tensorflow/tensorflow', 0.5939213633537292, 'ml-dl', 3), ('tensorflow/lucid', 0.5938147902488708, 'ml-interpretability', 1), ('nvidia/deeplearningexamples', 0.5919349193572998, 'ml-dl', 2), ('mdbloice/augmentor', 0.5899521708488464, 'ml', 2), ('pytorch/torchrec', 0.5860687494277954, 'ml-dl', 2), ('uber/petastorm', 0.5855341553688049, 'data', 3), ('nvlabs/gcvit', 0.5840114951133728, 'diffusion', 1), ('salesforce/blip', 0.5812243223190308, 'diffusion', 0), ('lutzroeder/netron', 0.5811353325843811, 'ml', 4), ('tensorflow/tensor2tensor', 0.5802233219146729, 'ml', 2), ('rasbt/deeplearning-models', 0.5799865126609802, 'ml-dl', 0), ('explosion/thinc', 0.5792794823646545, 'ml-dl', 3), ('mosaicml/composer', 0.5748881101608276, 'ml-dl', 4), ('pytorch/botorch', 0.5717622637748718, 'ml-dl', 0), ('microsoft/onnxruntime', 0.5676509141921997, 'ml', 3), ('tlkh/tf-metal-experiments', 0.5673794746398926, 'perf', 1), ('cvxgrp/pymde', 0.5655942559242249, 'ml', 2), ('aws/sagemaker-python-sdk', 0.5633373856544495, 'ml', 2), ('pytorch/pytorch', 0.5628584623336792, 'ml-dl', 3), ('blackhc/toma', 0.5623881220817566, 'ml-dl', 2), ('microsoft/deepspeed', 0.5605365037918091, 'ml-dl', 3), ('aistream-peelout/flow-forecast', 0.5596166253089905, 'time-series', 2), ('pyro-ppl/pyro', 0.5561047196388245, 'ml-dl', 3), ('nyandwi/modernconvnets', 0.5554874539375305, 'ml-dl', 0), ('rafiqhasan/auto-tensorflow', 0.5545974373817444, 'ml-dl', 1), ('hazyresearch/hgcn', 0.551753580570221, 'ml', 0), ('huggingface/huggingface_hub', 0.5494725108146667, 'ml', 3), ('google/tf-quant-finance', 0.5492528676986694, 'finance', 0), ('karpathy/mingpt', 0.548469066619873, 'llm', 0), ('kevinmusgrave/pytorch-metric-learning', 0.5479029417037964, 'ml', 3), ('davidmrau/mixture-of-experts', 0.5471916198730469, 'ml', 1), ('deci-ai/super-gradients', 0.5459545850753784, 'ml-dl', 3), ('huggingface/evaluate', 0.5455392003059387, 'ml', 1), ('fchollet/deep-learning-with-python-notebooks', 0.5449861288070679, 'study', 0), ('lucidrains/dalle2-pytorch', 0.5412147641181946, 'diffusion', 1), ('d2l-ai/d2l-en', 0.54007488489151, 'study', 3), ('tensorly/tensorly', 0.5390286445617676, 'ml-dl', 2), ('deepmind/dm-haiku', 0.5363015532493591, 'ml-dl', 2), ('graykode/nlp-tutorial', 0.5355981588363647, 'study', 1), ('speechbrain/speechbrain', 0.5351871848106384, 'nlp', 2), ('dmlc/dgl', 0.5350419878959656, 'ml-dl', 1), ('christoschristofidis/awesome-deep-learning', 0.5337355136871338, 'study', 3), ('qdrant/quaterion', 0.5309311747550964, 'ml', 3), ('huggingface/optimum', 0.5307228565216064, 'ml', 1), ('huggingface/diffusers', 0.528372049331665, 'diffusion', 2), ('tensorflow/addons', 0.5261369943618774, 'ml', 3), ('ddbourgin/numpy-ml', 0.5257222652435303, 'ml', 1), ('huggingface/datasets', 0.523903489112854, 'nlp', 3), ('optimalscale/lmflow', 0.5235216617584229, 'llm', 2), ('koaning/human-learn', 0.522743284702301, 'data', 1), ('salesforce/deeptime', 0.5224276185035706, 'time-series', 1), ('onnx/onnx', 0.521939218044281, 'ml', 4), ('humancompatibleai/imitation', 0.5217827558517456, 'ml-rl', 0), ('facebookresearch/dinov2', 0.5208505988121033, 'diffusion', 0), ('google-research/deeplab2', 0.5203951597213745, 'ml', 0), ('huggingface/peft', 0.5194254517555237, 'llm', 1), ('timdettmers/bitsandbytes', 0.5188927054405212, 'util', 0), ('tensorflow/data-validation', 0.5164223313331604, 'ml-ops', 0), ('kubeflow/fairing', 0.5159615874290466, 'ml-ops', 0), ('neuralmagic/deepsparse', 0.5143234133720398, 'nlp', 0), ('rwightman/pytorch-image-models', 0.512000322341919, 'ml-dl', 1), ('tensorflow/similarity', 0.5106225609779358, 'ml-dl', 2), ('facebookresearch/theseus', 0.5099302530288696, 'math', 2), ('keras-rl/keras-rl', 0.5081517696380615, 'ml-rl', 1), ('udacity/deep-learning-v2-pytorch', 0.5055270195007324, 'study', 3), ('keras-team/autokeras', 0.5053526759147644, 'ml-dl', 2), ('ray-project/ray', 0.504410982131958, 'ml-ops', 3), ('jeshraghian/snntorch', 0.5029792189598083, 'ml-dl', 2), ('kornia/kornia', 0.5025068521499634, 'ml-dl', 4), ('calculatedcontent/weightwatcher', 0.5007023811340332, 'ml-dl', 0), ('aiqc/aiqc', 0.5004318356513977, 'ml-ops', 0)]

204

7

null

2.77

115

105

75

0

3

115

53

90

0.5

53

43

data

https://github.com/lk-geimfari/mimesis

[]

null

[]

null

lk-geimfari/mimesis

mimesis

4,144

321

62

Python

https://mimesis.name

Mimesis is a powerful Python library that empowers developers to generate massive amounts of synthetic data efficiently.

lk-geimfari

2024-01-14

2016-09-09

385

10.747684

null

Mimesis is a powerful Python library that empowers developers to generate massive amounts of synthetic data efficiently.

['api-mock', 'data', 'dataframe', 'datascience', 'dummy', 'fake', 'faker', 'fixtures', 'generator', 'json', 'json-generator', 'mimesis', 'mock', 'pandas', 'polars', 'schema', 'syntetic', 'synthetic-data', 'testing']

2024-01-12

[('joke2k/faker', 0.6268561482429504, 'data', 3), ('getsentry/responses', 0.5823182463645935, 'testing', 0), ('python-odin/odin', 0.5751269459724426, 'util', 1), ('pytoolz/toolz', 0.5705004334449768, 'util', 0), ('marshmallow-code/marshmallow', 0.5606078505516052, 'util', 1), ('asacristani/fastapi-rocket-boilerplate', 0.5495461225509644, 'template', 0), ('snyk/faker-security', 0.5424483418464661, 'security', 0), ('fastai/fastcore', 0.5298691987991333, 'util', 0), ('pytables/pytables', 0.5296199321746826, 'data', 0), ('eleutherai/pyfra', 0.5290538668632507, 'ml', 0), ('nedbat/coveragepy', 0.5268024206161499, 'testing', 0), ('kubeflow/fairing', 0.5213274955749512, 'ml-ops', 0), ('falconry/falcon', 0.5205872654914856, 'web', 0), ('pyeve/cerberus', 0.5154099464416504, 'data', 0), ('brokenloop/jsontopydantic', 0.5148674845695496, 'util', 0), ('dagworks-inc/hamilton', 0.5131853222846985, 'ml-ops', 2), ('pypy/pypy', 0.5108677744865417, 'util', 0), ('unionai-oss/pandera', 0.509531557559967, 'pandas', 3), ('pandas-dev/pandas', 0.5089730024337769, 'pandas', 2), ('jsonpickle/jsonpickle', 0.5048171281814575, 'data', 1), ('tiangolo/sqlmodel', 0.5006476640701294, 'data', 1)]

117

4

null

4.63

51

44

89

0

11

9

11

51

73

90

1.4

53

335

ml

https://github.com/apple/coremltools

[]

null

[]

null

apple/coremltools

coremltools

3,860

581

116

Python

https://coremltools.readme.io

Core ML tools contain supporting tools for Core ML model conversion, editing, and validation.

apple

2024-01-14

2017-06-30

343

11.234927

https://avatars.githubusercontent.com/u/10639145?v=4

Core ML tools contain supporting tools for Core ML model conversion, editing, and validation.

['coreml', 'coremltools', 'machine-learning', 'model-conversion', 'model-converter', 'pytorch', 'tensorflow']

2024-01-10

[('huggingface/exporters', 0.6746289730072021, 'ml', 6), ('microsoft/nni', 0.5904099345207214, 'ml', 3), ('huggingface/datasets', 0.5799334049224854, 'nlp', 3), ('polyaxon/polyaxon', 0.5726978778839111, 'ml-ops', 3), ('selfexplainml/piml-toolbox', 0.558883786201477, 'ml-interpretability', 0), ('districtdatalabs/yellowbrick', 0.5530053377151489, 'ml', 1), ('keras-team/autokeras', 0.546789288520813, 'ml-dl', 2), ('deepchecks/deepchecks', 0.539066731929779, 'data', 2), ('lucidrains/toolformer-pytorch', 0.5380272269248962, 'llm', 0), ('nccr-itmo/fedot', 0.5334883332252502, 'ml-ops', 1), ('mosaicml/composer', 0.5304659605026245, 'ml-dl', 2), ('mlflow/mlflow', 0.5302109122276306, 'ml-ops', 1), ('onnx/onnx', 0.5105490684509277, 'ml', 3), ('wandb/client', 0.510352373123169, 'ml', 3), ('lutzroeder/netron', 0.5053067803382874, 'ml', 4), ('kubeflow/fairing', 0.5047186613082886, 'ml-ops', 0)]

159

3

null

2.06

127

82

80

0

6

126

286

90

2.3

53

252

ml

https://github.com/microsoft/flaml

[]

null

[]

null

microsoft/flaml

FLAML

3,493

488

56

Jupyter Notebook

https://microsoft.github.io/FLAML/

A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.

microsoft

2024-01-13

2020-08-20

179

19.436407

https://avatars.githubusercontent.com/u/6154722?v=4

A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.

['automated-machine-learning', 'automl', 'classification', 'data-science', 'deep-learning', 'finetuning', 'hyperparam', 'hyperparameter-optimization', 'jupyter-notebook', 'machine-learning', 'natural-language-generation', 'natural-language-processing', 'random-forest', 'regression', 'scikit-learn', 'tabular-data', 'timeseries-forecasting', 'tuning']

2023-11-29

[('mljar/mljar-supervised', 0.7940219044685364, 'ml', 7), ('microsoft/nni', 0.7865293025970459, 'ml', 6), ('keras-team/autokeras', 0.7519674897193909, 'ml-dl', 4), ('awslabs/autogluon', 0.7324180603027344, 'ml', 9), ('automl/auto-sklearn', 0.7281423807144165, 'ml', 4), ('shankarpandala/lazypredict', 0.6851475834846497, 'ml', 4), ('winedarksea/autots', 0.6591876745223999, 'time-series', 3), ('ray-project/tune-sklearn', 0.6497718095779419, 'ml', 2), ('nccr-itmo/fedot', 0.6372272372245789, 'ml-ops', 4), ('epistasislab/tpot', 0.6104899048805237, 'ml', 7), ('kubeflow/katib', 0.6054434776306152, 'ml', 0), ('featurelabs/featuretools', 0.6044269800186157, 'ml', 5), ('karpathy/micrograd', 0.5962915420532227, 'study', 0), ('determined-ai/determined', 0.5710462927818298, 'ml-ops', 4), ('huggingface/datasets', 0.5613746047019958, 'nlp', 3), ('alpa-projects/alpa', 0.5595440864562988, 'ml-dl', 2), ('ray-project/ray', 0.5589168667793274, 'ml-ops', 5), ('rafiqhasan/auto-tensorflow', 0.5583081841468811, 'ml-dl', 2), ('google/pyglove', 0.5550763607025146, 'util', 2), ('alkaline-ml/pmdarima', 0.5537622570991516, 'time-series', 1), ('huggingface/evaluate', 0.5472498536109924, 'ml', 1), ('ggerganov/ggml', 0.5470587611198425, 'ml', 1), ('salesforce/merlion', 0.5453396439552307, 'time-series', 2), ('google/vizier', 0.5446196794509888, 'ml', 4), ('firmai/atspy', 0.5425217747688293, 'time-series', 0), ('huggingface/autotrain-advanced', 0.5361581444740295, 'ml', 3), ('uber/petastorm', 0.5358170866966248, 'data', 2), ('rasbt/mlxtend', 0.5349463224411011, 'ml', 2), ('scikit-optimize/scikit-optimize', 0.5336490869522095, 'ml', 3), ('xplainable/xplainable', 0.5324146747589111, 'ml-interpretability', 2), ('autoviml/auto_ts', 0.5320088863372803, 'time-series', 1), ('hiyouga/llama-factory', 0.5290379524230957, 'llm', 0), ('hiyouga/llama-efficient-tuning', 0.5290378928184509, 'llm', 0), ('rasbt/machine-learning-book', 0.5261116623878479, 'study', 3), ('tensorflow/tensor2tensor', 0.5255224704742432, 'ml', 2), ('neuralmagic/sparseml', 0.525197446346283, 'ml-dl', 1), ('ashleve/lightning-hydra-template', 0.5247229337692261, 'util', 1), ('koaning/human-learn', 0.5246617197990417, 'data', 2), ('explosion/thinc', 0.5239095091819763, 'ml-dl', 3), ('tensorflow/data-validation', 0.5238473415374756, 'ml-ops', 0), ('huggingface/transformers', 0.5236698985099792, 'nlp', 3), ('gradio-app/gradio', 0.5217346549034119, 'viz', 3), ('aws/sagemaker-python-sdk', 0.5215294361114502, 'ml', 1), ('wandb/client', 0.5212470293045044, 'ml', 4), ('tigerlab-ai/tiger', 0.5200607180595398, 'llm', 1), ('teamhg-memex/eli5', 0.5194395184516907, 'ml', 3), ('ourownstory/neural_prophet', 0.5170196294784546, 'ml', 2), ('districtdatalabs/yellowbrick', 0.5168565511703491, 'ml', 2), ('patchy631/machine-learning', 0.5163537263870239, 'ml', 0), ('nixtla/statsforecast', 0.5162665843963623, 'time-series', 3), ('ml-tooling/opyrator', 0.5143886804580688, 'viz', 1), ('sktime/sktime', 0.5142588019371033, 'time-series', 3), ('optuna/optuna', 0.5139668583869934, 'ml', 2), ('catboost/catboost', 0.5135185122489929, 'ml', 2), ('oml-team/open-metric-learning', 0.5119624733924866, 'ml', 2), ('google/temporian', 0.511090874671936, 'time-series', 0), ('linkedin/greykite', 0.5093781352043152, 'ml', 0), ('ageron/handson-ml2', 0.5074008107185364, 'ml', 0), ('pycaret/pycaret', 0.5066448450088501, 'ml', 4), ('selfexplainml/piml-toolbox', 0.5052233338356018, 'ml-interpretability', 0), ('huggingface/peft', 0.5017809867858887, 'llm', 0), ('merantix-momentum/squirrel-core', 0.5003235340118408, 'ml', 4), ('polyaxon/polyaxon', 0.5002272129058838, 'ml-ops', 4)]

80

4

null

2.98

31

13

41

2

18

20

18

31

50

90

1.6

53

472

nlp

https://github.com/neuralmagic/deepsparse

[]

null

[]

null

neuralmagic/deepsparse

deepsparse

2,707

160

53

Python

https://neuralmagic.com/deepsparse/

Sparsity-aware deep learning inference runtime for CPUs

neuralmagic

2024-01-13

2020-12-14

163

16.59282

https://avatars.githubusercontent.com/u/68670575?v=4

Sparsity-aware deep learning inference runtime for CPUs

['computer-vision', 'cpus', 'deepsparse', 'inference', 'llm-inference', 'machinelearning', 'nlp', 'object-detection', 'onnx', 'performance', 'pretrained-models', 'pruning', 'quantization', 'sparsification']

2024-01-10

[('neuralmagic/sparseml', 0.7135436534881592, 'ml-dl', 5), ('microsoft/deepspeed', 0.643064022064209, 'ml-dl', 1), ('microsoft/onnxruntime', 0.6196989417076111, 'ml', 1), ('alpa-projects/alpa', 0.6077420711517334, 'ml-dl', 0), ('lutzroeder/netron', 0.5835353136062622, 'ml', 2), ('huggingface/datasets', 0.5752450823783875, 'nlp', 2), ('tlkh/tf-metal-experiments', 0.5730476379394531, 'perf', 0), ('mosaicml/composer', 0.5704326033592224, 'ml-dl', 0), ('squeezeailab/squeezellm', 0.5691953301429749, 'llm', 1), ('intel/intel-extension-for-pytorch', 0.5653654932975769, 'perf', 1), ('bigscience-workshop/petals', 0.5630180835723877, 'data', 2), ('keras-team/keras', 0.5612209439277649, 'ml-dl', 0), ('onnx/onnx', 0.5601222515106201, 'ml', 1), ('aiqc/aiqc', 0.556576669216156, 'ml-ops', 0), ('nvidia/deeplearningexamples', 0.554892361164093, 'ml-dl', 2), ('determined-ai/determined', 0.5497815608978271, 'ml-ops', 0), ('huggingface/optimum', 0.5494052171707153, 'ml', 3), ('vllm-project/vllm', 0.5437913537025452, 'llm', 1), ('nyandwi/modernconvnets', 0.5420705080032349, 'ml-dl', 1), ('explosion/thinc', 0.5401971936225891, 'ml-dl', 1), ('apache/incubator-mxnet', 0.53566974401474, 'ml-dl', 0), ('facebookresearch/ppuda', 0.5350483059883118, 'ml-dl', 0), ('tensorflow/tensorflow', 0.5337933301925659, 'ml-dl', 0), ('huggingface/transformers', 0.532548189163208, 'nlp', 2), ('tensorflow/tensor2tensor', 0.5306204557418823, 'ml', 0), ('rwightman/pytorch-image-models', 0.5303251147270203, 'ml-dl', 1), ('horovod/horovod', 0.5292316675186157, 'ml-ops', 1), ('roboflow/supervision', 0.5291524529457092, 'ml', 2), ('deepfakes/faceswap', 0.5284426212310791, 'ml-dl', 0), ('ddbourgin/numpy-ml', 0.5217757225036621, 'ml', 0), ('pytorch/glow', 0.514583945274353, 'ml', 0), ('pytorch/ignite', 0.5143234133720398, 'ml-dl', 0), ('calculatedcontent/weightwatcher', 0.5087005496025085, 'ml-dl', 0), ('paddlepaddle/paddle', 0.5083123445510864, 'ml-dl', 0), ('rasbt/machine-learning-book', 0.5080384612083435, 'study', 0), ('blackhc/toma', 0.5067216753959656, 'ml-dl', 0), ('cvxgrp/pymde', 0.5062499642372131, 'ml', 0), ('pytorchlightning/pytorch-lightning', 0.5051679015159607, 'ml-dl', 0), ('megvii-basedetection/yolox', 0.5051378607749939, 'ml', 2), ('polyaxon/polyaxon', 0.504664957523346, 'ml-ops', 0), ('ludwig-ai/ludwig', 0.5014819502830505, 'ml-ops', 2), ('facebookresearch/pytorch3d', 0.5011691451072693, 'ml-dl', 0), ('fepegar/torchio', 0.5005324482917786, 'ml-dl', 0)]

41

3

null

8.13

222

202

38

0

10

12

10

222

98

90

0.4

53

539

data

https://github.com/sqlalchemy/alembic

[]

null

[]

null

sqlalchemy/alembic

alembic

2,302

211

19

Python

null

A database migrations tool for SQLAlchemy.

sqlalchemy

2024-01-13

2018-11-27

270

8.525926

https://avatars.githubusercontent.com/u/6043126?v=4

A database migrations tool for SQLAlchemy.

['sql', 'sqlalchemy']

2024-01-13

[('sqlalchemy/sqlalchemy', 0.8273295164108276, 'data', 2), ('agronholm/sqlacodegen', 0.6634976267814636, 'data', 0), ('mause/duckdb_engine', 0.6483481526374817, 'data', 2), ('tiangolo/sqlmodel', 0.6223205924034119, 'data', 2), ('aminalaee/sqladmin', 0.5552855730056763, 'data', 1), ('ibis-project/ibis', 0.5510525107383728, 'data', 2), ('aeternalis-ingenium/fastapi-backend-template', 0.5487288236618042, 'web', 1), ('mcfunley/pugsql', 0.5098458528518677, 'data', 1)]

181

5

null

2.63

84

64

62

0

16

24

16

84

228

90

2.7

53

1,689

util

https://github.com/pypa/setuptools

['setuptools', 'build']

null

[]

null

pypa/setuptools

setuptools

2,224

1,095

93

Python

https://pypi.org/project/setuptools/

Official project repository for the Setuptools build system

pypa

2024-01-12

2016-03-29

409

5.437653

https://avatars.githubusercontent.com/u/647025?v=4

Official project repository for the Setuptools build system

[]

['build', 'setuptools']

2024-01-11

[('pyo3/setuptools-rust', 0.6672810912132263, 'util', 2)]

587

4

null

15.08

145

71

95

0

28

83

28

146

273

90

1.9

53

1,898

pandas

https://github.com/delta-io/delta-rs

['databricks', 'rust']

null

[]

null

delta-io/delta-rs

delta-rs

1,620

305

38

Rust

https://delta-io.github.io/delta-rs/

A native Rust library for Delta Lake, with bindings into Python

delta-io

2024-01-16

2020-04-26

196

8.253275

https://avatars.githubusercontent.com/u/49767398?v=4

A native Rust library for Delta Lake, with bindings into Python

['databricks', 'delta', 'delta-lake', 'pandas', 'pandas-dataframe', 'rust']

2024-01-16

[('eventual-inc/daft', 0.6028104424476624, 'pandas', 1), ('pola-rs/polars', 0.596839427947998, 'pandas', 1), ('sfu-db/connector-x', 0.5911102890968323, 'data', 1), ('pyo3/pyo3', 0.5582752227783203, 'util', 1), ('tkrabel/bamboolib', 0.5383087396621704, 'pandas', 1), ('pyo3/maturin', 0.532139241695404, 'util', 1), ('rustpython/rustpython', 0.5259521007537842, 'util', 1), ('pyo3/rust-numpy', 0.5224049687385559, 'util', 1), ('pandas-dev/pandas', 0.5217164754867554, 'pandas', 1), ('geopandas/geopandas', 0.5198134183883667, 'gis', 1), ('mito-ds/monorepo', 0.503544807434082, 'jupyter', 1), ('pytoolz/toolz', 0.5006144642829895, 'util', 0)]

128

3

null

9.9

455

310

45

0

24

18

24

455

994

90

2.2

53

630

util

https://github.com/pygments/pygments

[]

null

[]

null

pygments/pygments

pygments

1,487

579

33

Python

http://pygments.org/

Pygments is a generic syntax highlighter written in Python

pygments

2024-01-13

2019-08-31

230

6.453193

https://avatars.githubusercontent.com/u/50935516?v=4

Pygments is a generic syntax highlighter written in Python

['syntax-highlighting']

2024-01-13

[('hhatto/autopep8', 0.600104570388794, 'util', 0), ('grantjenks/blue', 0.5901092886924744, 'util', 0), ('pypy/pypy', 0.5847700834274292, 'util', 0), ('python/cpython', 0.5650127530097961, 'util', 0), ('willmcgugan/rich', 0.5573404431343079, 'term', 1), ('google/yapf', 0.5552298426628113, 'util', 0), ('instagram/libcst', 0.5501353144645691, 'util', 0), ('pyglet/pyglet', 0.5452966094017029, 'gamedev', 0), ('pycqa/pylint-django', 0.5438166856765747, 'util', 0), ('google/latexify_py', 0.5412126183509827, 'util', 0), ('hoffstadt/dearpygui', 0.5314857959747314, 'gui', 0), ('python-markdown/markdown', 0.5284628868103027, 'util', 0), ('psf/black', 0.5274278521537781, 'util', 0), ('landscapeio/prospector', 0.5254445672035217, 'util', 0), ('pyston/pyston', 0.5150144696235657, 'util', 0), ('webpy/webpy', 0.5060795545578003, 'web', 0), ('pypi/warehouse', 0.5018252730369568, 'util', 0), ('pytoolz/toolz', 0.5010949969291687, 'util', 0), ('brandtbucher/specialist', 0.5001950263977051, 'perf', 0)]

821

5

null

7.12

137

107

53

0

7

15

7

137

282

90

2.1

53

1,558

ml

https://github.com/huggingface/huggingface_hub

[]

null

[]

null

huggingface/huggingface_hub

huggingface_hub

1,449

354

58

Python

https://huggingface.co/docs/huggingface_hub

The official Python client for the Huggingface Hub.

huggingface

2024-01-14

2020-12-22

162

8.944444

https://avatars.githubusercontent.com/u/25720743?v=4

The official Python client for the Huggingface Hub.

['deep-learning', 'machine-learning', 'model-hub', 'models', 'natural-language-processing', 'pretrained-models', 'pytorch']

2024-01-12

[('skorch-dev/skorch', 0.6804894804954529, 'ml-dl', 2), ('aws/sagemaker-python-sdk', 0.6623826026916504, 'ml', 2), ('huggingface/exporters', 0.6611513495445251, 'ml', 3), ('kubeflow/fairing', 0.624878466129303, 'ml-ops', 0), ('huggingface/transformers', 0.6154810190200806, 'nlp', 6), ('gradio-app/gradio', 0.6130750775337219, 'viz', 3), ('radiantearth/radiant-mlhub', 0.6118897199630737, 'gis', 1), ('rasbt/machine-learning-book', 0.6020623445510864, 'study', 3), ('huggingface/datasets', 0.5904778242111206, 'nlp', 4), ('huggingface/notebooks', 0.5788795948028564, 'ml', 0), ('intel/intel-extension-for-pytorch', 0.5788046717643738, 'perf', 3), ('hugapi/hug', 0.5746172070503235, 'util', 0), ('skops-dev/skops', 0.5664080381393433, 'ml-ops', 1), ('dylanhogg/awesome-python', 0.5635517835617065, 'study', 3), ('merantix-momentum/squirrel-core', 0.5627287030220032, 'ml', 4), ('uber/petastorm', 0.5579898357391357, 'data', 3), ('ashleve/lightning-hydra-template', 0.5572559237480164, 'util', 2), ('openai/openai-python', 0.5553815960884094, 'util', 0), ('huggingface/deep-rl-class', 0.5541204810142517, 'study', 1), ('hoffstadt/dearpygui', 0.5539893507957458, 'gui', 0), ('ageron/handson-ml2', 0.5522385835647583, 'ml', 0), ('pytorch/ignite', 0.5494725108146667, 'ml-dl', 3), ('deepfakes/faceswap', 0.5489972233772278, 'ml-dl', 2), ('dmlc/dgl', 0.5465887784957886, 'ml-dl', 1), ('fchollet/deep-learning-with-python-notebooks', 0.5410536527633667, 'study', 0), ('ddbourgin/numpy-ml', 0.5406401753425598, 'ml', 1), ('tensorly/tensorly', 0.5400019884109497, 'ml-dl', 2), ('allenai/allennlp', 0.5300591588020325, 'nlp', 3), ('googleapis/google-api-python-client', 0.5284603238105774, 'util', 0), ('iperov/deepfacelab', 0.5282143950462341, 'ml-dl', 2), ('tensorlayer/tensorlayer', 0.5281078815460205, 'ml-rl', 1), ('fastai/fastcore', 0.5268593430519104, 'util', 0), ('mrdbourke/pytorch-deep-learning', 0.5265445113182068, 'study', 3), ('featurelabs/featuretools', 0.5263670682907104, 'ml', 1), ('ta-lib/ta-lib-python', 0.5248498916625977, 'finance', 0), ('pypy/pypy', 0.5246903896331787, 'util', 0), ('nvidia/deeplearningexamples', 0.5234879851341248, 'ml-dl', 2), ('pyg-team/pytorch_geometric', 0.5223245620727539, 'ml-dl', 2), ('beeware/toga', 0.5219206213951111, 'gui', 0), ('timofurrer/awesome-asyncio', 0.5210409164428711, 'study', 0), ('alibaba/easynlp', 0.5210217237472534, 'nlp', 4), ('ggerganov/ggml', 0.5206968188285828, 'ml', 1), ('huggingface/autotrain-advanced', 0.5198477506637573, 'ml', 3), ('facebookresearch/pytorch3d', 0.5197669863700867, 'ml-dl', 0), ('selfexplainml/piml-toolbox', 0.5193759202957153, 'ml-interpretability', 0), ('weaviate/weaviate-python-client', 0.5164599418640137, 'util', 0), ('google/temporian', 0.5130770802497864, 'time-series', 0), ('ml-tooling/opyrator', 0.5117499828338623, 'viz', 1), ('eleutherai/pyfra', 0.5113564133644104, 'ml', 0), ('python/cpython', 0.5113198757171631, 'util', 0), ('nielsrogge/transformers-tutorials', 0.5096057057380676, 'study', 1), ('willmcgugan/textual', 0.5090726613998413, 'term', 0), ('lucidrains/toolformer-pytorch', 0.5079225301742554, 'llm', 1), ('nvlabs/gcvit', 0.5078686475753784, 'diffusion', 1), ('xl0/lovely-tensors', 0.5074052214622498, 'ml-dl', 2), ('pytorch/rl', 0.5057786703109741, 'ml-rl', 2), ('lightly-ai/lightly', 0.5056184530258179, 'ml', 3), ('adap/flower', 0.5031947493553162, 'ml-ops', 3), ('numpy/numpy', 0.5030168890953064, 'math', 0), ('speechbrain/speechbrain', 0.5026688575744629, 'nlp', 2), ('pycaret/pycaret', 0.5024893283843994, 'ml', 1), ('microsoft/onnxruntime', 0.5021616816520691, 'ml', 3), ('probml/pyprobml', 0.5018727779388428, 'ml', 2), ('mdbloice/augmentor', 0.5017703175544739, 'ml', 2), ('arogozhnikov/einops', 0.5012728571891785, 'ml-dl', 2), ('wandb/client', 0.5004013180732727, 'ml', 3), ('alphasecio/langchain-examples', 0.5002479553222656, 'llm', 0), ('nevronai/metisfl', 0.5000477433204651, 'ml', 2)]

127

2

null

7.19

267

213

37

0

25

32

25

265

759

90

2.9

53

1,724

llm

https://github.com/ray-project/ray-llm

[]

null

[]

null

ray-project/ray-llm

ray-llm

949

61

21

Python

https://aviary.anyscale.com

RayLLM - LLMs on Ray

ray-project

2024-01-13

2023-05-31

34

27.22541

https://avatars.githubusercontent.com/u/22125274?v=4

RayLLM - LLMs on Ray

['distributed-systems', 'large-language-models', 'llm', 'llm-inference', 'llm-serving', 'llmops', 'ray', 'serving', 'transformers']

2024-01-08

[('vllm-project/vllm', 0.7471011877059937, 'llm', 3), ('bentoml/openllm', 0.6621026396751404, 'ml-ops', 4), ('predibase/lorax', 0.6269615888595581, 'llm', 5), ('artidoro/qlora', 0.6143306493759155, 'llm', 0), ('salesforce/xgen', 0.6136285662651062, 'llm', 2), ('ray-project/ray-educational-materials', 0.6102384924888611, 'study', 4), ('bigscience-workshop/petals', 0.6017612218856812, 'data', 2), ('bobazooba/xllm', 0.5996918082237244, 'llm', 2), ('sjtu-ipads/powerinfer', 0.5986047387123108, 'llm', 3), ('young-geng/easylm', 0.5914445519447327, 'llm', 1), ('eugeneyan/open-llms', 0.5834382772445679, 'study', 2), ('explosion/spacy-llm', 0.5664099454879761, 'llm', 2), ('microsoft/torchscale', 0.5647855997085571, 'llm', 0), ('iryna-kondr/scikit-llm', 0.5598890781402588, 'llm', 2), ('ray-project/ray', 0.5598110556602478, 'ml-ops', 3), ('nomic-ai/gpt4all', 0.5573980808258057, 'llm', 1), ('mooler0410/llmspracticalguide', 0.5559900999069214, 'study', 1), ('microsoft/jarvis', 0.5456799268722534, 'llm', 0), ('squeezeailab/squeezellm', 0.5445480942726135, 'llm', 2), ('microsoft/autogen', 0.5439698100090027, 'llm', 2), ('nebuly-ai/nebullvm', 0.5362703800201416, 'perf', 2), ('cg123/mergekit', 0.5349216461181641, 'llm', 1), ('hiyouga/llama-factory', 0.5283878445625305, 'llm', 3), ('hiyouga/llama-efficient-tuning', 0.528387725353241, 'llm', 3), ('deepset-ai/haystack', 0.5249264240264893, 'llm', 2), ('citadel-ai/langcheck', 0.524300754070282, 'llm', 0), ('deep-diver/pingpong', 0.5193211436271667, 'llm', 0), ('titanml/takeoff', 0.5190406441688538, 'llm', 1), ('thudm/chatglm2-6b', 0.5179040431976318, 'llm', 2), ('intel/intel-extension-for-transformers', 0.5162841081619263, 'perf', 1), ('agenta-ai/agenta', 0.5125582218170166, 'llm', 3), ('next-gpt/next-gpt', 0.5125154256820679, 'llm', 2), ('lianjiatech/belle', 0.5085573792457581, 'llm', 0), ('opengvlab/omniquant', 0.5080553293228149, 'llm', 2), ('jina-ai/thinkgpt', 0.5078703165054321, 'llm', 0), ('juncongmoo/pyllama', 0.505372941493988, 'llm', 0), ('dylanhogg/llmgraph', 0.5024334192276001, 'ml', 1)]

21

5

null

3.06

54

20

8

0

10

15

10

54

56

90

1

53

688

ml-dl

https://github.com/iperov/deepfacelab

[]

null

[]

null

iperov/deepfacelab

DeepFaceLab

44,089

9,977

1,114

Python

null

DeepFaceLab is the leading software for creating deepfakes.

iperov

2024-01-14

2018-06-04

295

149.381897

null

DeepFaceLab is the leading software for creating deepfakes.

['arxiv', 'creating-deepfakes', 'deep-face-swap', 'deep-learning', 'deep-neural-networks', 'deepface', 'deepfacelab', 'deepfakes', 'deeplearning', 'face-swap', 'faceswap', 'fakeapp', 'machine-learning', 'neural-nets', 'neural-networks']

2023-04-27

[('deepfakes/faceswap', 0.8627434968948364, 'ml-dl', 12), ('nvidia/deeplearningexamples', 0.5346398949623108, 'ml-dl', 1), ('open-mmlab/mmediting', 0.5308938026428223, 'ml', 1), ('huggingface/huggingface_hub', 0.5282143950462341, 'ml', 2), ('rwightman/pytorch-image-models', 0.5256627798080444, 'ml-dl', 0), ('fepegar/torchio', 0.5164421200752258, 'ml-dl', 2), ('deepchecks/deepchecks', 0.515143871307373, 'data', 2), ('deepmind/deepmind-research', 0.5150367021560669, 'ml', 0), ('huggingface/datasets', 0.5133152008056641, 'nlp', 2), ('microsoft/deepspeed', 0.5126926302909851, 'ml-dl', 2), ('alpa-projects/alpa', 0.511199414730072, 'ml-dl', 2), ('awslabs/autogluon', 0.5111877918243408, 'ml', 2), ('christoschristofidis/awesome-deep-learning', 0.5062230825424194, 'study', 2), ('neuralmagic/sparseml', 0.5047088861465454, 'ml-dl', 0), ('keras-team/autokeras', 0.5044635534286499, 'ml-dl', 2)]

22

0

null

0.02

11

2

68

9

0

11

5

90

0.5

52

933

llm

https://github.com/karpathy/mingpt

[]

null

[]

null

karpathy/mingpt

minGPT

17,452

2,101

249

Python

null

A minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training

karpathy

2024-01-14

2020-08-17

180

96.878668

null

A minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training

[]

2023-01-08

[('ist-daslab/gptq', 0.7072771787643433, 'llm', 0), ('minimaxir/gpt-2-simple', 0.6132301688194275, 'llm', 0), ('nvidia/apex', 0.6042015552520752, 'ml-dl', 0), ('bigscience-workshop/megatron-deepspeed', 0.6039530634880066, 'llm', 0), ('microsoft/megatron-deepspeed', 0.6039530634880066, 'llm', 0), ('nielsrogge/transformers-tutorials', 0.6038249135017395, 'study', 0), ('huggingface/optimum', 0.5994217395782471, 'ml', 0), ('pytorch-labs/gpt-fast', 0.5887901782989502, 'llm', 0), ('nvlabs/gcvit', 0.5820482969284058, 'diffusion', 0), ('huggingface/transformers', 0.5732393860816956, 'nlp', 0), ('eleutherai/gpt-neo', 0.5706537961959839, 'llm', 0), ('eleutherai/gpt-neox', 0.5511136651039124, 'llm', 0), ('karpathy/nanogpt', 0.5497898459434509, 'llm', 0), ('pytorch/ignite', 0.548469066619873, 'ml-dl', 0), ('explosion/spacy-transformers', 0.5479704141616821, 'llm', 0), ('alignmentresearch/tuned-lens', 0.5471770763397217, 'ml-interpretability', 0), ('huggingface/accelerate', 0.5470962524414062, 'ml', 0), ('eleutherai/knowledge-neurons', 0.5461640954017639, 'ml-interpretability', 0), ('promptslab/awesome-prompt-engineering', 0.5419448018074036, 'study', 0), ('nvidia/megatron-lm', 0.5354270935058594, 'llm', 0), ('mrdbourke/pytorch-deep-learning', 0.5222852230072021, 'study', 0), ('lucidrains/vit-pytorch', 0.5179693102836609, 'ml-dl', 0), ('intel/intel-extension-for-pytorch', 0.5158076882362366, 'perf', 0), ('openai/image-gpt', 0.5077084302902222, 'llm', 0), ('apple/ml-ane-transformers', 0.5006250143051147, 'ml', 0)]

15

4

null

0

5

1

42

12

0

5

4

90

0.8

52

505

ml

https://github.com/tensorflow/tensor2tensor

[]

null

[]

null

tensorflow/tensor2tensor

tensor2tensor

14,478

3,407

468

Python

null

Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.

tensorflow

2024-01-14

2017-06-15

345

41.878512

https://avatars.githubusercontent.com/u/15658638?v=4

Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.

['deep-learning', 'machine-learning', 'machine-translation', 'reinforcement-learning', 'tpu']

2023-04-01

[('tensorlayer/tensorlayer', 0.6871770024299622, 'ml-rl', 2), ('huggingface/datasets', 0.6564465761184692, 'nlp', 2), ('tensorflow/tensorflow', 0.6497355103492737, 'ml-dl', 2), ('unity-technologies/ml-agents', 0.6379924416542053, 'ml-rl', 3), ('microsoft/deepspeed', 0.6303361058235168, 'ml-dl', 2), ('explosion/thinc', 0.626385509967804, 'ml-dl', 2), ('nvidia/deeplearningexamples', 0.6179958581924438, 'ml-dl', 1), ('google/trax', 0.615790605545044, 'ml-dl', 3), ('keras-rl/keras-rl', 0.6136747002601624, 'ml-rl', 2), ('denys88/rl_games', 0.6038516163825989, 'ml-rl', 2), ('mosaicml/composer', 0.5954499244689941, 'ml-dl', 2), ('deepmind/dm_control', 0.5927808880805969, 'ml-rl', 3), ('d2l-ai/d2l-en', 0.5922254920005798, 'study', 3), ('keras-team/autokeras', 0.5915209650993347, 'ml-dl', 2), ('rasbt/machine-learning-book', 0.5888902544975281, 'study', 2), ('determined-ai/determined', 0.5887267589569092, 'ml-ops', 2), ('google-research/google-research', 0.5845038890838623, 'ml', 1), ('keras-team/keras', 0.5834200382232666, 'ml-dl', 2), ('salesforce/warp-drive', 0.5827850699424744, 'ml-rl', 2), ('firmai/industry-machine-learning', 0.5822129249572754, 'study', 1), ('pytorch/ignite', 0.5802233219146729, 'ml-dl', 2), ('uber/petastorm', 0.5750295519828796, 'data', 2), ('rasbt/deeplearning-models', 0.5731253623962402, 'ml-dl', 0), ('openai/spinningup', 0.5718406438827515, 'study', 0), ('thu-ml/tianshou', 0.5683255791664124, 'ml-rl', 0), ('alirezadir/machine-learning-interview-enlightener', 0.5649195909500122, 'study', 2), ('microsoft/onnxruntime', 0.564765214920044, 'ml', 2), ('mlflow/mlflow', 0.5625280737876892, 'ml-ops', 1), ('microsoft/nni', 0.5608126521110535, 'ml', 2), ('google-research/language', 0.5586530566215515, 'nlp', 1), ('ddbourgin/numpy-ml', 0.5577438473701477, 'ml', 2), ('lutzroeder/netron', 0.5569348335266113, 'ml', 2), ('udlbook/udlbook', 0.5561156868934631, 'study', 1), ('microsoft/jarvis', 0.5555034279823303, 'llm', 1), ('aiqc/aiqc', 0.5551923513412476, 'ml-ops', 0), ('facebookresearch/habitat-lab', 0.5538010597229004, 'sim', 2), ('mrdbourke/pytorch-deep-learning', 0.5526059865951538, 'study', 2), ('alpa-projects/alpa', 0.5523074865341187, 'ml-dl', 2), ('onnx/onnx', 0.5511443018913269, 'ml', 2), ('ray-project/ray', 0.5493798851966858, 'ml-ops', 3), ('bentoml/bentoml', 0.5486508011817932, 'ml-ops', 2), ('ageron/handson-ml2', 0.5483447313308716, 'ml', 0), ('merantix-momentum/squirrel-core', 0.5476986765861511, 'ml', 2), ('deepchecks/deepchecks', 0.5471684336662292, 'data', 2), ('ml-for-high-risk-apps-book/machine-learning-for-high-risk-applications-book', 0.5430309772491455, 'study', 2), ('deepmodeling/deepmd-kit', 0.5421066880226135, 'sim', 1), ('allenai/allennlp', 0.5407803058624268, 'nlp', 1), ('fepegar/torchio', 0.5404090285301208, 'ml-dl', 2), ('pytorch/rl', 0.539577305316925, 'ml-rl', 2), ('apache/incubator-mxnet', 0.5354474186897278, 'ml-dl', 0), ('tensorflow/data-validation', 0.5354011654853821, 'ml-ops', 0), ('salesforce/deeptime', 0.5346342325210571, 'time-series', 1), ('cerlymarco/medium_notebook', 0.5338510870933533, 'study', 2), ('paddlepaddle/paddle', 0.5337570905685425, 'ml-dl', 2), ('oegedijk/explainerdashboard', 0.5324363708496094, 'ml-interpretability', 0), ('ashleve/lightning-hydra-template', 0.5318635106086731, 'util', 1), ('neuralmagic/deepsparse', 0.5306204557418823, 'nlp', 0), ('google/dopamine', 0.5282601118087769, 'ml-rl', 0), ('deeppavlov/deeppavlov', 0.5281538963317871, 'nlp', 2), ('huggingface/transformers', 0.5262730717658997, 'nlp', 2), ('microsoft/flaml', 0.5255224704742432, 'ml', 2), ('intellabs/bayesian-torch', 0.5250702500343323, 'ml', 1), ('koaning/human-learn', 0.5240030884742737, 'data', 1), ('tatsu-lab/stanford_alpaca', 0.5224913954734802, 'llm', 1), ('ggerganov/ggml', 0.519944965839386, 'ml', 1), ('googlecloudplatform/vertex-ai-samples', 0.5193653702735901, 'ml', 0), ('xplainable/xplainable', 0.5187652707099915, 'ml-interpretability', 1), ('hpcaitech/colossalai', 0.5182396173477173, 'llm', 1), ('neuralmagic/sparseml', 0.5167617201805115, 'ml-dl', 0), ('aistream-peelout/flow-forecast', 0.5155697464942932, 'time-series', 1), ('gradio-app/gradio', 0.5152331590652466, 'viz', 2), ('google/vizier', 0.5147285461425781, 'ml', 2), ('oml-team/open-metric-learning', 0.5146539211273193, 'ml', 1), ('aws/sagemaker-python-sdk', 0.5145456790924072, 'ml', 1), ('deepmind/dm-haiku', 0.5139560103416443, 'ml-dl', 2), ('xl0/lovely-tensors', 0.5108433961868286, 'ml-dl', 1), ('microsoft/qlib', 0.5105899572372437, 'finance', 2), ('udacity/deep-learning-v2-pytorch', 0.5104150176048279, 'study', 1), ('activeloopai/deeplake', 0.5102148652076721, 'ml-ops', 2), ('azavea/raster-vision', 0.5076959133148193, 'gis', 2), ('karpathy/micrograd', 0.5075839757919312, 'study', 0), ('facebookresearch/theseus', 0.5072576403617859, 'math', 1), ('project-monai/monai', 0.5071702599525452, 'ml', 1), ('csinva/imodels', 0.5070091485977173, 'ml', 1), ('pytorchlightning/pytorch-lightning', 0.5069326758384705, 'ml-dl', 2), ('intel/intel-extension-for-pytorch', 0.5063350200653076, 'perf', 2), ('polyaxon/polyaxon', 0.5061532258987427, 'ml-ops', 3), ('amanchadha/coursera-deep-learning-specialization', 0.5060564875602722, 'study', 1), ('horovod/horovod', 0.5053731799125671, 'ml-ops', 2), ('optimalscale/lmflow', 0.5030723810195923, 'llm', 1), ('interpretml/interpret', 0.5023159980773926, 'ml-interpretability', 1)]

244

7

null

0.02

0

80

10

0

12

0

90

0

52

1,644

util

https://github.com/dbader/schedule

['scheduler']

null

[]

1

null

dbader/schedule

schedule

11,297

996

216

Python

https://schedule.readthedocs.io/

Python job scheduling for humans.

dbader

2024-01-13

2013-05-19

558

20.235159

null

Python job scheduling for humans.

[]

['scheduler']

2023-12-10

[('agronholm/apscheduler', 0.7123571634292603, 'util', 0), ('dask/dask', 0.5425211191177368, 'perf', 0), ('pyinvoke/invoke', 0.514901876449585, 'util', 0)]

59

5

null

0.27

16

6

130

1

0

2

16

29

90

1.8

52

166

nlp

https://github.com/doccano/doccano

[]

null

[]

null

doccano/doccano

doccano

8,649

1,653

129

Python

https://doccano.herokuapp.com

Open source annotation tool for machine learning practitioners.

doccano

2024-01-14

2018-05-09

298

28.940249

https://avatars.githubusercontent.com/u/58067660?v=4

Open source annotation tool for machine learning practitioners.

['annotation-tool', 'data-labeling', 'dataset', 'datasets', 'machine-learning', 'natural-language-processing', 'nuxt', 'nuxtjs', 'text-annotation', 'vue', 'vuejs']

2023-08-10

[('argilla-io/argilla', 0.6546259522438049, 'nlp', 4), ('mlflow/mlflow', 0.6210007667541504, 'ml-ops', 1), ('hegelai/prompttools', 0.6014738082885742, 'llm', 1), ('rasahq/rasa', 0.5829582214355469, 'llm', 2), ('tensorflow/tensorflow', 0.5740697383880615, 'ml-dl', 1), ('microsoft/nni', 0.573647141456604, 'ml', 1), ('tigerlab-ai/tiger', 0.5629643797874451, 'llm', 0), ('wandb/client', 0.5617552399635315, 'ml', 1), ('polyaxon/polyaxon', 0.5601885914802551, 'ml-ops', 1), ('cleanlab/cleanlab', 0.5571958422660828, 'ml', 2), ('alirezadir/machine-learning-interview-enlightener', 0.5449758768081665, 'study', 1), ('aimhubio/aim', 0.5435435771942139, 'ml-ops', 1), ('huggingface/datasets', 0.5418587923049927, 'nlp', 3), ('patchy631/machine-learning', 0.5417935848236084, 'ml', 0), ('ai4finance-foundation/fingpt', 0.5407078862190247, 'finance', 1), ('onnx/onnx', 0.5324045419692993, 'ml', 1), ('google-research/language', 0.5283976197242737, 'nlp', 2), ('polyaxon/datatile', 0.5258282423019409, 'pandas', 0), ('nltk/nltk', 0.5226835608482361, 'nlp', 2), ('determined-ai/determined', 0.5204253196716309, 'ml-ops', 1), ('districtdatalabs/yellowbrick', 0.5116096138954163, 'ml', 1), ('featurelabs/featuretools', 0.5110718607902527, 'ml', 1), ('firmai/industry-machine-learning', 0.50450199842453, 'study', 1)]

104

4

null

1.87

49

9

69

5

1

6

1

49

62

90

1.3

52

28

ml-dl

https://github.com/google/trax

[]

null

[]

null

google/trax

trax

7,858

818

148

Python

null

Trax — Deep Learning with Clear Code and Speed

google

2024-01-14

2019-10-05

225

34.858048

https://avatars.githubusercontent.com/u/1342004?v=4

Trax — Deep Learning with Clear Code and Speed

['deep-learning', 'deep-reinforcement-learning', 'jax', 'machine-learning', 'numpy', 'reinforcement-learning', 'transformer']

2023-11-15

[('keras-team/keras', 0.7093995809555054, 'ml-dl', 3), ('keras-rl/keras-rl', 0.6790956258773804, 'ml-rl', 2), ('tensorlayer/tensorlayer', 0.6657304167747498, 'ml-rl', 2), ('explosion/thinc', 0.6631956696510315, 'ml-dl', 3), ('huggingface/transformers', 0.659750759601593, 'nlp', 4), ('deepmind/dm-haiku', 0.6491378545761108, 'ml-dl', 3), ('denys88/rl_games', 0.6481664776802063, 'ml-rl', 2), ('ddbourgin/numpy-ml', 0.6432744264602661, 'ml', 2), ('salesforce/warp-drive', 0.640018880367279, 'ml-rl', 2), ('deepmind/dm_control', 0.6313595771789551, 'ml-rl', 3), ('thu-ml/tianshou', 0.625861406326294, 'ml-rl', 0), ('tensorflow/tensor2tensor', 0.615790605545044, 'ml', 3), ('tensorflow/tensorflow', 0.6033942103385925, 'ml-dl', 2), ('unity-technologies/ml-agents', 0.5988940596580505, 'ml-rl', 4), ('pytorch/rl', 0.5977087020874023, 'ml-rl', 2), ('microsoft/deepspeed', 0.5964576601982117, 'ml-dl', 2), ('alpa-projects/alpa', 0.5918993949890137, 'ml-dl', 3), ('d2l-ai/d2l-en', 0.587719202041626, 'study', 4), ('apache/incubator-mxnet', 0.583592414855957, 'ml-dl', 0), ('mosaicml/composer', 0.5817326307296753, 'ml-dl', 2), ('nvidia/deeplearningexamples', 0.5805593132972717, 'ml-dl', 1), ('onnx/onnx', 0.5766066908836365, 'ml', 2), ('kzl/decision-transformer', 0.5694336891174316, 'ml-rl', 0), ('ray-project/ray', 0.568706214427948, 'ml-ops', 3), ('ai4finance-foundation/finrl', 0.5627601146697998, 'finance', 2), ('gradio-app/gradio', 0.5625860095024109, 'viz', 2), ('microsoft/onnxruntime', 0.5622458457946777, 'ml', 2), ('aiqc/aiqc', 0.555395245552063, 'ml-ops', 0), ('pytorchlightning/pytorch-lightning', 0.550957202911377, 'ml-dl', 2), ('determined-ai/determined', 0.5475213527679443, 'ml-ops', 2), ('huggingface/optimum', 0.5470688343048096, 'ml', 0), ('ml-tooling/opyrator', 0.5450164079666138, 'viz', 1), ('pyro-ppl/pyro', 0.539913535118103, 'ml-dl', 2), ('huggingface/datasets', 0.5373858213424683, 'nlp', 3), ('arogozhnikov/einops', 0.5327727198600769, 'ml-dl', 3), ('openai/baselines', 0.5311444401741028, 'ml-rl', 0), ('karpathy/micrograd', 0.5311139822006226, 'study', 0), ('keras-team/autokeras', 0.5302404761314392, 'ml-dl', 2), ('deepmodeling/deepmd-kit', 0.5293905735015869, 'sim', 1), ('google/flax', 0.5265333652496338, 'ml-dl', 1), ('microsoft/nni', 0.5194593071937561, 'ml', 2), ('deepmind/pysc2', 0.5190588235855103, 'ml-rl', 2), ('thilinarajapakse/simpletransformers', 0.5190243721008301, 'nlp', 0), ('bigscience-workshop/petals', 0.5161072611808777, 'data', 3), ('ludwig-ai/ludwig', 0.5144282579421997, 'ml-ops', 2), ('koaning/human-learn', 0.514390230178833, 'data', 1), ('tlkh/tf-metal-experiments', 0.5128339529037476, 'perf', 1), ('bentoml/bentoml', 0.5128212571144104, 'ml-ops', 2), ('ml-for-high-risk-apps-book/machine-learning-for-high-risk-applications-book', 0.512615442276001, 'study', 2), ('modularml/mojo', 0.5107121467590332, 'util', 1), ('uber/petastorm', 0.5106483101844788, 'data', 2), ('awslabs/autogluon', 0.5100558996200562, 'ml', 2), ('google/dopamine', 0.5098437666893005, 'ml-rl', 0), ('online-ml/river', 0.5071595311164856, 'ml', 1), ('pytorch/pytorch', 0.5070921778678894, 'ml-dl', 3), ('inspirai/timechamber', 0.5059916377067566, 'sim', 2), ('huggingface/autotrain-advanced', 0.5045042037963867, 'ml', 2), ('facebookresearch/habitat-lab', 0.5037897825241089, 'sim', 3), ('young-geng/easylm', 0.5037261843681335, 'llm', 3), ('wandb/client', 0.502128541469574, 'ml', 4), ('rwightman/pytorch-image-models', 0.5016557574272156, 'ml-dl', 0), ('xplainable/xplainable', 0.5001837015151978, 'ml-interpretability', 1)]

79

5

null

0.1

8

3

52

2

0

4

8

4

90

0.5

52

646

profiling

https://github.com/joerick/pyinstrument

[]

null

[]

null

joerick/pyinstrument

pyinstrument

5,802

235

53

Python

https://pyinstrument.readthedocs.io/

🚴 Call stack profiler for Python. Shows you why your code is slow!

joerick

2024-01-13

2014-03-13

515

11.250416

null

🚴 Call stack profiler for Python. Shows you why your code is slow!

['async', 'django', 'performance', 'profile', 'profiler']

2024-01-06

[('sumerc/yappi', 0.6088473200798035, 'profiling', 2), ('benfred/py-spy', 0.5834751129150391, 'profiling', 1), ('jiffyclub/snakeviz', 0.5636839866638184, 'profiling', 0), ('pythonspeed/filprofiler', 0.5218971967697144, 'profiling', 0), ('pyutils/line_profiler', 0.5132960677146912, 'profiling', 0)]

55

7

null

1.98

18

10

120

0

5

6

5

18

34

90

1.9

52

1,167

study

https://github.com/gkamradt/langchain-tutorials

[]

null

[]

null

gkamradt/langchain-tutorials

langchain-tutorials

5,691

1,717

97

Jupyter Notebook

null

Overview and tutorial of the LangChain Library

gkamradt

2024-01-14

2023-02-13

50

113.495726

null

Overview and tutorial of the LangChain Library

[]

2023-11-23

[('prefecthq/langchain-prefect', 0.7797976732254028, 'llm', 0), ('langchain-ai/langgraph', 0.6401094794273376, 'llm', 0), ('logspace-ai/langflow', 0.5531355142593384, 'llm', 0), ('alphasecio/langchain-examples', 0.5529564023017883, 'llm', 0), ('langchain-ai/chat-langchain', 0.5390220284461975, 'llm', 0), ('langchain-ai/langsmith-sdk', 0.5348765254020691, 'llm', 0), ('hannibal046/awesome-llm', 0.5057912468910217, 'study', 0)]

17

4

null

1.75

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0

11

2

0

1

0

90

0

52

15

ml-dl

https://github.com/skorch-dev/skorch

[]

null

[]

null

skorch-dev/skorch

skorch

5,518

379

82

Jupyter Notebook

null

A scikit-learn compatible neural network library that wraps PyTorch

skorch-dev

2024-01-13

2017-07-18

341

16.181818

https://avatars.githubusercontent.com/u/47992320?v=4

A scikit-learn compatible neural network library that wraps PyTorch

['huggingface', 'machine-learning', 'pytorch', 'scikit-learn']

2024-01-08

[('pytorch/ignite', 0.8268391489982605, 'ml-dl', 2), ('rasbt/machine-learning-book', 0.777802050113678, 'study', 3), ('intel/intel-extension-for-pytorch', 0.7512941360473633, 'perf', 2), ('mrdbourke/pytorch-deep-learning', 0.6955669522285461, 'study', 2), ('nvidia/apex', 0.6882312893867493, 'ml-dl', 0), ('huggingface/huggingface_hub', 0.6804894804954529, 'ml', 2), ('pyg-team/pytorch_geometric', 0.6679598093032837, 'ml-dl', 1), ('karpathy/micrograd', 0.644400417804718, 'study', 0), ('allenai/allennlp', 0.639916181564331, 'nlp', 1), ('pytorch/data', 0.631018877029419, 'data', 0), ('pytorch/rl', 0.6245636940002441, 'ml-rl', 2), ('hysts/pytorch_image_classification', 0.619719386100769, 'ml-dl', 1), ('pytorch/captum', 0.6131489276885986, 'ml-interpretability', 0), ('xl0/lovely-tensors', 0.612391471862793, 'ml-dl', 1), ('huggingface/accelerate', 0.6029394268989563, 'ml', 0), ('ashleve/lightning-hydra-template', 0.6017202138900757, 'util', 1), ('huggingface/transformers', 0.6005750894546509, 'nlp', 2), ('arogozhnikov/einops', 0.599236786365509, 'ml-dl', 1), ('ggerganov/ggml', 0.5978483557701111, 'ml', 1), ('neuralmagic/sparseml', 0.5961683988571167, 'ml-dl', 1), ('ageron/handson-ml2', 0.5958633422851562, 'ml', 0), ('lucidrains/imagen-pytorch', 0.5915490388870239, 'ml-dl', 0), ('denys88/rl_games', 0.5850237011909485, 'ml-rl', 1), ('facebookresearch/pytorch3d', 0.5811278223991394, 'ml-dl', 0), ('aws/sagemaker-python-sdk', 0.5779036283493042, 'ml', 3), ('lightly-ai/lightly', 0.5767190456390381, 'ml', 2), ('rentruewang/koila', 0.5766161680221558, 'ml', 2), ('nicolas-chaulet/torch-points3d', 0.5687388777732849, 'ml', 0), ('microsoft/onnxruntime', 0.5680661797523499, 'ml', 3), ('tensorlayer/tensorlayer', 0.5663044452667236, 'ml-rl', 0), ('koaning/human-learn', 0.5661436319351196, 'data', 2), ('koaning/scikit-lego', 0.5642397999763489, 'ml', 2), ('speechbrain/speechbrain', 0.5581321120262146, 'nlp', 2), ('intellabs/bayesian-torch', 0.5576133131980896, 'ml', 1), ('laekov/fastmoe', 0.5523069500923157, 'ml', 0), ('facebookresearch/dinov2', 0.5518595576286316, 'diffusion', 0), ('mdbloice/augmentor', 0.5499297976493835, 'ml', 1), ('uber/petastorm', 0.5473853945732117, 'data', 2), ('tensorflow/tensorflow', 0.5416784286499023, 'ml-dl', 1), ('determined-ai/determined', 0.5415751338005066, 'ml-ops', 2), ('thu-ml/tianshou', 0.5379747152328491, 'ml-rl', 1), ('lucidrains/dalle2-pytorch', 0.5362039804458618, 'diffusion', 0), ('kshitij12345/torchnnprofiler', 0.5358409881591797, 'profiling', 0), ('cvxgrp/pymde', 0.5335275530815125, 'ml', 2), ('huggingface/exporters', 0.532882034778595, 'ml', 2), ('horovod/horovod', 0.5322457551956177, 'ml-ops', 2), ('nvlabs/gcvit', 0.531648576259613, 'diffusion', 0), ('pytorch/pytorch', 0.5300707817077637, 'ml-dl', 1), ('ddbourgin/numpy-ml', 0.526438295841217, 'ml', 1), ('aistream-peelout/flow-forecast', 0.5259057879447937, 'time-series', 1), ('explosion/thinc', 0.525391161441803, 'ml-dl', 2), ('salesforce/blip', 0.5246773362159729, 'diffusion', 0), ('tensorflow/lucid', 0.5241331458091736, 'ml-interpretability', 1), ('lutzroeder/netron', 0.5238518714904785, 'ml', 2), ('nvidia/deeplearningexamples', 0.5229756832122803, 'ml-dl', 1), ('tensorly/tensorly', 0.5220605134963989, 'ml-dl', 2), ('pytorch/torchrec', 0.5207085609436035, 'ml-dl', 1), ('oml-team/open-metric-learning', 0.5191598534584045, 'ml', 1), ('iryna-kondr/scikit-llm', 0.5175820589065552, 'llm', 2), ('fchollet/deep-learning-with-python-notebooks', 0.5172905325889587, 'study', 0), ('jeshraghian/snntorch', 0.5167255401611328, 'ml-dl', 2), ('pycaret/pycaret', 0.5164783000946045, 'ml', 1), ('tlkh/tf-metal-experiments', 0.5154433250427246, 'perf', 0), ('keras-team/keras', 0.5138635635375977, 'ml-dl', 2), ('rdkit/rdkit', 0.510020911693573, 'sim', 0), ('nyandwi/modernconvnets', 0.509011447429657, 'ml-dl', 0), ('davidmrau/mixture-of-experts', 0.5069704055786133, 'ml', 1), ('salesforce/deeptime', 0.506636381149292, 'time-series', 0), ('huggingface/datasets', 0.5065990686416626, 'nlp', 2), ('qdrant/quaterion', 0.506058394908905, 'ml', 2), ('pytorch/glow', 0.5048933029174805, 'ml', 0), ('deepmodeling/deepmd-kit', 0.5047734379768372, 'sim', 0), ('probml/pyprobml', 0.5041447877883911, 'ml', 2), ('pytorch/botorch', 0.5020517110824585, 'ml-dl', 0), ('gradio-app/gradio', 0.5019252896308899, 'viz', 1), ('rasbt/mlxtend', 0.5017459988594055, 'ml', 1), ('tensorflow/similarity', 0.5013630986213684, 'ml-dl', 1), ('kubeflow/fairing', 0.501205325126648, 'ml-ops', 0), ('dmlc/dgl', 0.5011494755744934, 'ml-dl', 0)]

61

5

null

0.96

18

13

79

0

3

18

29

90

1.6

52

823

typing

https://github.com/python-attrs/attrs

[]

null

[]

1

null

python-attrs/attrs

attrs

4,977

388

65

Python

https://www.attrs.org/

Python Classes Without Boilerplate

python-attrs

2024-01-13

2015-01-27

470

10.589362

https://avatars.githubusercontent.com/u/25880274?v=4

Python Classes Without Boilerplate

['attributes', 'boilerplate', 'classes', 'oop']

2024-01-13

[('martinheinz/python-project-blueprint', 0.521111011505127, 'template', 1), ('landscapeio/prospector', 0.5136226415634155, 'util', 0), ('xrudelis/pytrait', 0.5021693110466003, 'util', 0)]

154

3

null

3.29

49

36

109

0

2

3

2

49

124

90

2.5

52

213

data

https://github.com/facebookresearch/augly

[]

null

[]

null

facebookresearch/augly

AugLy

4,853

295

67

Python

https://ai.facebook.com/blog/augly-a-new-data-augmentation-library-to-help-build-more-robust-ai-models/

A data augmentations library for audio, image, text, and video.

facebookresearch

2024-01-12

2021-06-09

137

35.203109

https://avatars.githubusercontent.com/u/16943930?v=4

A data augmentations library for audio, image, text, and video.

[]

2023-11-08

[('albumentations-team/albumentations', 0.6632611751556396, 'ml-dl', 0), ('mdbloice/augmentor', 0.6478663086891174, 'ml', 0), ('aleju/imgaug', 0.5716978311538696, 'ml', 0), ('nomic-ai/nomic', 0.528243899345398, 'nlp', 0), ('researchmm/sttn', 0.5215305089950562, 'ml-dl', 0)]

34

3

null

0.21

6

2

32

2

0

3

6

14

90

2.3

52

92

ml

https://github.com/uber/causalml

[]

null

[]

null

uber/causalml

causalml

4,514

753

80

Python

null

Uplift modeling and causal inference with machine learning algorithms

uber

2024-01-13

2019-07-09

238

18.966387

https://avatars.githubusercontent.com/u/538264?v=4

Uplift modeling and causal inference with machine learning algorithms

['causal-inference', 'incubation', 'machine-learning', 'uplift-modeling']

2024-01-12

[('py-why/econml', 0.5542822480201721, 'ml', 2)]

59

4

null

1.6

90

74

55

0

2

3

2

90

1

52

199

viz

https://github.com/man-group/dtale

[]

null

[]

null

man-group/dtale

dtale

4,398

371

73

TypeScript

http://alphatechadmin.pythonanywhere.com

Visualizer for pandas data structures

man-group

2024-01-14

2019-07-15

237

18.545783

https://avatars.githubusercontent.com/u/5859004?v=4

Visualizer for pandas data structures

['data-analysis', 'data-science', 'data-visualization', 'flask', 'ipython', 'jupyter-notebook', 'pandas', 'plotly-dash', 'python27', 'react', 'react-virtualized', 'visualization', 'xarray']

2024-01-05

[('mwaskom/seaborn', 0.73142409324646, 'viz', 3), ('holoviz/panel', 0.7240487337112427, 'viz', 0), ('kanaries/pygwalker', 0.7181293368339539, 'pandas', 3), ('lux-org/lux', 0.7073760032653809, 'viz', 3), ('holoviz/holoviz', 0.7002979516983032, 'viz', 0), ('bokeh/bokeh', 0.6867046356201172, 'viz', 1), ('plotly/plotly.py', 0.6799153089523315, 'viz', 3), ('plotly/dash', 0.6759928464889526, 'viz', 5), ('residentmario/geoplot', 0.6714649796485901, 'gis', 0), ('holoviz/hvplot', 0.6696478724479675, 'pandas', 0), ('pandas-dev/pandas', 0.6628751754760742, 'pandas', 3), ('altair-viz/altair', 0.6516591310501099, 'viz', 1), ('jakevdp/pythondatasciencehandbook', 0.6342079639434814, 'study', 2), ('pyqtgraph/pyqtgraph', 0.6243569850921631, 'viz', 1), ('tkrabel/bamboolib', 0.6187593936920166, 'pandas', 2), ('enthought/mayavi', 0.6186628937721252, 'viz', 1), ('adamerose/pandasgui', 0.6185036897659302, 'pandas', 1), ('vizzuhq/ipyvizzu', 0.6090724468231201, 'jupyter', 3), ('vaexio/vaex', 0.6020064353942871, 'perf', 2), ('wesm/pydata-book', 0.5984211564064026, 'study', 0), ('polyaxon/datatile', 0.5954803824424744, 'pandas', 3), ('scitools/iris', 0.5857634544372559, 'gis', 1), ('mckinsey/vizro', 0.584793746471405, 'viz', 3), ('graphistry/pygraphistry', 0.5765081644058228, 'data', 2), ('has2k1/plotnine', 0.5764876008033752, 'viz', 1), ('federicoceratto/dashing', 0.5763976573944092, 'term', 0), ('matplotlib/matplotlib', 0.5757876634597778, 'viz', 2), ('rapidsai/cudf', 0.5755491256713867, 'pandas', 3), ('maartenbreddels/ipyvolume', 0.5735721588134766, 'jupyter', 1), ('krzjoa/awesome-python-data-science', 0.5704981088638306, 'study', 3), ('contextlab/hypertools', 0.5685189366340637, 'ml', 2), ('quantopian/qgrid', 0.560211718082428, 'jupyter', 0), ('lutzroeder/netron', 0.5549408793449402, 'ml', 0), ('hazyresearch/meerkat', 0.5547817945480347, 'viz', 2), ('ranaroussi/quantstats', 0.55287766456604, 'finance', 1), ('cuemacro/chartpy', 0.5520331263542175, 'viz', 0), ('mito-ds/monorepo', 0.5518519282341003, 'jupyter', 4), ('opengeos/leafmap', 0.5516546368598938, 'gis', 2), ('gregorhd/mapcompare', 0.5462871789932251, 'gis', 0), ('holoviz/datashader', 0.5459538698196411, 'gis', 0), ('dylanhogg/awesome-python', 0.5450599193572998, 'study', 2), ('ydataai/ydata-profiling', 0.5416145324707031, 'pandas', 4), ('scikit-hep/awkward-1.0', 0.5412405729293823, 'data', 2), ('datapane/datapane', 0.5396667718887329, 'viz', 1), ('giswqs/geemap', 0.5396121144294739, 'gis', 2), ('pyvista/pyvista', 0.5372913479804993, 'viz', 1), ('vispy/vispy', 0.5336646437644958, 'viz', 1), ('matplotlib/mplfinance', 0.5290730595588684, 'finance', 0), ('dagworks-inc/hamilton', 0.525833010673523, 'ml-ops', 3), ('python-odin/odin', 0.5247855186462402, 'util', 0), ('holoviz/spatialpandas', 0.5217031240463257, 'pandas', 1), ('holoviz/geoviews', 0.5216120481491089, 'gis', 0), ('geopandas/geopandas', 0.5202478766441345, 'gis', 1), ('pola-rs/polars', 0.5197016596794128, 'pandas', 0), ('scitools/cartopy', 0.519442617893219, 'gis', 0), ('raphaelquast/eomaps', 0.5189169049263, 'gis', 1), ('districtdatalabs/yellowbrick', 0.5179511308670044, 'ml', 1), ('saulpw/visidata', 0.5157226324081421, 'term', 1), ('python-visualization/folium', 0.5144950747489929, 'gis', 2), ('eleutherai/pyfra', 0.5136914253234863, 'ml', 0), ('twopirllc/pandas-ta', 0.5126270651817322, 'finance', 2), ('unionai-oss/pandera', 0.5104021430015564, 'pandas', 1), ('marcomusy/vedo', 0.5097540020942688, 'viz', 1), ('visgl/deck.gl', 0.5085725784301758, 'viz', 2), ('hi-primus/optimus', 0.5049717426300049, 'ml-ops', 2), ('tokern/data-lineage', 0.5029366612434387, 'data', 0), ('imageio/imageio', 0.5025433897972107, 'util', 0), ('koaning/drawdata', 0.5000766515731812, 'jupyter', 0)]

30

2

null

2.42

30

18

55

0

30

37

30

42

90

1.4

52

1,779

viz

https://github.com/renpy/renpy

[]

null

[]

null

renpy/renpy

renpy

4,311

648

144

Ren'Py

http://www.renpy.org/

The Ren'Py Visual Novel Engine

renpy

2024-01-14

2012-06-28

604

7.128987

https://avatars.githubusercontent.com/u/1900740?v=4

The Ren'Py Visual Novel Engine

['engine', 'game', 'novel', 'renpy', 'visual', 'visual-novel']

2024-01-14

[('pokepetter/ursina', 0.6157830357551575, 'gamedev', 0), ('kitao/pyxel', 0.5945414304733276, 'gamedev', 1), ('pygame/pygame', 0.5524816513061523, 'gamedev', 0), ('panda3d/panda3d', 0.5438269972801208, 'gamedev', 0), ('pyscript/pyscript-cli', 0.5380860567092896, 'web', 0), ('fastai/fastcore', 0.5279468894004822, 'util', 0), ('python/cpython', 0.5222944617271423, 'util', 0), ('hoffstadt/dearpygui', 0.5120179057121277, 'gui', 0), ('mynameisfiber/high_performance_python_2e', 0.5067214369773865, 'study', 0), ('zulko/moviepy', 0.5059114098548889, 'util', 0), ('gradio-app/gradio', 0.5017328858375549, 'viz', 0), ('amaargiru/pyroad', 0.500852644443512, 'study', 0)]

194

1

null

31.38

346

293

141

0

8

47

8

345

606

90

1.8

52

356

data

https://github.com/amundsen-io/amundsen

[]

null

[]

null

amundsen-io/amundsen

amundsen

4,179

947

237

Python

https://www.amundsen.io/amundsen/

Amundsen is a metadata driven application for improving the productivity of data analysts, data scientists and engineers when interacting with data.

amundsen-io

2024-01-13

2019-05-14

246

16.987805

https://avatars.githubusercontent.com/u/67136999?v=4

Amundsen is a metadata driven application for improving the productivity of data analysts, data scientists and engineers when interacting with data.

['amundsen', 'data-catalog', 'data-discovery', 'linuxfoundation', 'metadata']

2024-01-11

[]

222

2

null

1.42

36

21

57

0

7

28

7

36

42

90

1.2

52

755

sim

https://github.com/quantumlib/cirq

[]

null

[]

null

quantumlib/cirq

Cirq

4,027

948

192

Python

null

A python framework for creating, editing, and invoking Noisy Intermediate Scale Quantum (NISQ) circuits.

quantumlib

2024-01-14

2017-12-14

319

12.595621

https://avatars.githubusercontent.com/u/31279789?v=4

A python framework for creating, editing, and invoking Noisy Intermediate Scale Quantum (NISQ) circuits.

['cirq', 'nisq', 'quantum-algorithms', 'quantum-circuits', 'quantum-computing']

2024-01-13

[('cqcl/lambeq', 0.6558890342712402, 'nlp', 0), ('pyscf/pyscf', 0.6541039347648621, 'sim', 0), ('cqcl/tket', 0.6193458437919617, 'util', 1), ('jackhidary/quantumcomputingbook', 0.5691633224487305, 'study', 2), ('qiskit/qiskit', 0.5546154975891113, 'sim', 1), ('netket/netket', 0.5286350250244141, 'sim', 0), ('zeromq/pyzmq', 0.5248025059700012, 'util', 0)]

213

2

null

4.87

166

98

74

0

2

4

2

166

243

90

1.5

52

802

web

https://github.com/fastapi-users/fastapi-users

[]

null

[]

null

fastapi-users/fastapi-users

fastapi-users

3,772

341

38

Python

https://fastapi-users.github.io/fastapi-users/

Ready-to-use and customizable users management for FastAPI

fastapi-users

2024-01-14

2019-10-05

225

16.732573

https://avatars.githubusercontent.com/u/89578248?v=4

Ready-to-use and customizable users management for FastAPI

['async', 'asyncio', 'fastapi', 'fastapi-users', 'starlette', 'users']

2023-12-28

[('dmontagu/fastapi_client', 0.6202594637870789, 'web', 0), ('zhanymkanov/fastapi-best-practices', 0.6014936566352844, 'study', 1), ('tiangolo/fastapi', 0.599251925945282, 'web', 4), ('s3rius/fastapi-template', 0.595072329044342, 'web', 2), ('fastapi-admin/fastapi-admin', 0.5555592775344849, 'web', 1), ('asacristani/fastapi-rocket-boilerplate', 0.5379810333251953, 'template', 1), ('aminalaee/sqladmin', 0.5336757302284241, 'data', 3), ('awtkns/fastapi-crudrouter', 0.5089220404624939, 'web', 3), ('starlite-api/starlite', 0.5006967186927795, 'web', 1)]

62

4

null

1.1

20

15

52

1

9

23

9

20

35

90

1.8

52

171

ml

https://github.com/ourownstory/neural_prophet

[]

null

[]

null

ourownstory/neural_prophet

neural_prophet

3,494

453

53

Python

https://neuralprophet.com

NeuralProphet: A simple forecasting package

ourownstory

2024-01-12

2020-05-04

195

17.904832

null

NeuralProphet: A simple forecasting package

['artificial-intelligence', 'autoregression', 'deep-learning', 'fbprophet', 'forecast', 'forecasting', 'forecasting-algorithm', 'forecasting-model', 'machine-learning', 'neural', 'neural-network', 'neuralprophet', 'prediction', 'prophet', 'pytorch', 'seasonality', 'time-series', 'timeseries', 'trend']

2023-12-23

[('winedarksea/autots', 0.6846452355384827, 'time-series', 4), ('nixtla/statsforecast', 0.6677179336547852, 'time-series', 6), ('awslabs/autogluon', 0.6234149932861328, 'ml', 5), ('salesforce/deeptime', 0.5901058316230774, 'time-series', 3), ('aistream-peelout/flow-forecast', 0.5880416035652161, 'time-series', 4), ('microprediction/microprediction', 0.5824498534202576, 'time-series', 3), ('uber/orbit', 0.5688930153846741, 'time-series', 5), ('awslabs/gluonts', 0.5649511814117432, 'time-series', 7), ('firmai/atspy', 0.5586233735084534, 'time-series', 2), ('microsoft/nni', 0.5511186718940735, 'ml', 4), ('alkaline-ml/pmdarima', 0.5404297709465027, 'time-series', 3), ('nccr-itmo/fedot', 0.5363118648529053, 'ml-ops', 1), ('nvidia/deeplearningexamples', 0.5321094989776611, 'ml-dl', 3), ('mosaicml/composer', 0.5314452052116394, 'ml-dl', 4), ('sktime/sktime', 0.529460608959198, 'time-series', 3), ('ddbourgin/numpy-ml', 0.5267665982246399, 'ml', 1), ('activeloopai/deeplake', 0.524020791053772, 'ml-ops', 3), ('salesforce/merlion', 0.5225098133087158, 'time-series', 3), ('mindsdb/mindsdb', 0.5187014937400818, 'data', 4), ('microsoft/flaml', 0.5170196294784546, 'ml', 2), ('xplainable/xplainable', 0.5147477984428406, 'ml-interpretability', 2), ('opengeos/earthformer', 0.5128765106201172, 'gis', 2), ('keras-team/autokeras', 0.5104817748069763, 'ml-dl', 2), ('huggingface/transformers', 0.5077774524688721, 'nlp', 3), ('automl/auto-sklearn', 0.5033456683158875, 'ml', 0), ('alirezadir/machine-learning-interview-enlightener', 0.503267228603363, 'study', 2), ('explosion/thinc', 0.501133382320404, 'ml-dl', 4)]

50

2

null

3.35

65

48

45

1

11

8

11

65

107

90

1.6

52

1,635

util

https://github.com/osohq/oso

['authorization']

null

[]

null

osohq/oso

oso

3,335

169

31

Rust

https://docs.osohq.com

Oso is a batteries-included framework for building authorization in your application.

osohq

2024-01-14

2020-05-04

195

17.090044

https://avatars.githubusercontent.com/u/47367300?v=4

Oso is a batteries-included framework for building authorization in your application.

['abac', 'access-control', 'authorization', 'authorization-framework', 'go', 'java', 'logic-programming', 'nodejs', 'policy-engine', 'rbac', 'rbac-authorization', 'rbac-roles', 'ruby', 'rust', 'security']

2024-01-13

[]

66

5

null

0.81

17

8

45

0

7

54

7

17

27

90

1.6

52

267

jupyter

https://github.com/jupyterlab/jupyterlab-desktop

[]

null

[]

null

jupyterlab/jupyterlab-desktop

jupyterlab-desktop

3,199

297

52

TypeScript

null

JupyterLab desktop application, based on Electron.

jupyterlab

2024-01-12

2017-05-04

351

9.095451

https://avatars.githubusercontent.com/u/22800682?v=4

JupyterLab desktop application, based on Electron.

['jupyter', 'jupyter-notebook', 'jupyterlab']

2024-01-05

[('jupyterlab/jupyterlab', 0.7525447607040405, 'jupyter', 2), ('voila-dashboards/voila', 0.7262636423110962, 'jupyter', 2), ('jupyter/notebook', 0.7161470651626587, 'jupyter', 2), ('jupyter-widgets/ipywidgets', 0.7082852721214294, 'jupyter', 0), ('jupyter/nbformat', 0.6620615720748901, 'jupyter', 0), ('mwouts/jupytext', 0.6525211930274963, 'jupyter', 2), ('aws/graph-notebook', 0.6357448697090149, 'jupyter', 2), ('maartenbreddels/ipyvolume', 0.6347945928573608, 'jupyter', 2), ('jupyter/nbconvert', 0.6312793493270874, 'jupyter', 0), ('jupyterlite/jupyterlite', 0.6264117956161499, 'jupyter', 2), ('vizzuhq/ipyvizzu', 0.6113208532333374, 'jupyter', 2), ('ipython/ipykernel', 0.6094779968261719, 'util', 2), ('cohere-ai/notebooks', 0.5881903767585754, 'llm', 0), ('ipython/ipyparallel', 0.5839833617210388, 'perf', 1), ('jupyter-widgets/ipyleaflet', 0.5790235996246338, 'gis', 1), ('jupyter-lsp/jupyterlab-lsp', 0.5716159343719482, 'jupyter', 3), ('computationalmodelling/nbval', 0.5705468654632568, 'jupyter', 1), ('bloomberg/ipydatagrid', 0.5657516717910767, 'jupyter', 0), ('quantopian/qgrid', 0.5566320419311523, 'jupyter', 0), ('mamba-org/gator', 0.5549662709236145, 'jupyter', 1), ('jupyter/nbdime', 0.552423357963562, 'jupyter', 2), ('jakevdp/pythondatasciencehandbook', 0.5509034395217896, 'study', 1), ('fchollet/deep-learning-with-python-notebooks', 0.5508671402931213, 'study', 0), ('tkrabel/bamboolib', 0.5493032336235046, 'pandas', 2), ('xiaohk/stickyland', 0.5476192235946655, 'jupyter', 2), ('holoviz/panel', 0.5330305695533752, 'viz', 1), ('nteract/testbook', 0.5236980319023132, 'jupyter', 1), ('r0x0r/pywebview', 0.520444393157959, 'gui', 0), ('giswqs/mapwidget', 0.5143319964408875, 'gis', 1), ('ageron/handson-ml2', 0.510633647441864, 'ml', 0), ('rapidsai/jupyterlab-nvdashboard', 0.5053638815879822, 'jupyter', 0), ('jupyter/nbviewer', 0.5004984736442566, 'jupyter', 2)]

39

5

null

4.31

52

37

82

0

11

5

11

52

113

90

2.2

52

807

data

https://github.com/deepchecks/deepchecks

[]

null

[]

null

deepchecks/deepchecks

deepchecks

3,169

229

16

Python

https://docs.deepchecks.com/stable

Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling to thoroughly test your data and models from research to production.

deepchecks

2024-01-13

2021-10-11

120

26.376932

https://avatars.githubusercontent.com/u/92298186?v=4

Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling to thoroughly test your data and models from research to production.

['data-drift', 'data-science', 'data-validation', 'deep-learning', 'html-report', 'jupyter-notebook', 'machine-learning', 'ml', 'mlops', 'model-monitoring', 'model-validation', 'pandas-dataframe', 'pytorch']

2023-12-18

[('evidentlyai/evidently', 0.6157994866371155, 'ml-ops', 8), ('polyaxon/polyaxon', 0.5667403340339661, 'ml-ops', 6), ('microsoft/deepspeed', 0.5651904940605164, 'ml-dl', 3), ('determined-ai/determined', 0.5619574189186096, 'ml-ops', 5), ('huggingface/datasets', 0.5608824491500854, 'nlp', 3), ('wandb/client', 0.557380735874176, 'ml', 5), ('giskard-ai/giskard', 0.550081193447113, 'data', 3), ('tensorflow/tensor2tensor', 0.5471684336662292, 'ml', 2), ('tensorflow/tensorflow', 0.5415099859237671, 'ml-dl', 3), ('mlflow/mlflow', 0.5400528907775879, 'ml-ops', 2), ('microsoft/nni', 0.5397449731826782, 'ml', 5), ('mosaicml/composer', 0.5395089387893677, 'ml-dl', 3), ('apple/coremltools', 0.539066731929779, 'ml', 2), ('nvidia/deeplearningexamples', 0.537693440914154, 'ml-dl', 2), ('unity-technologies/ml-agents', 0.5319340825080872, 'ml-rl', 2), ('googlecloudplatform/vertex-ai-samples', 0.5285258889198303, 'ml', 3), ('polyaxon/datatile', 0.5274471640586853, 'pandas', 3), ('bentoml/bentoml', 0.5182715058326721, 'ml-ops', 3), ('iperov/deepfacelab', 0.515143871307373, 'ml-dl', 2), ('explosion/thinc', 0.5133498311042786, 'ml-dl', 3), ('uber/petastorm', 0.5133116245269775, 'data', 3), ('tensorflow/data-validation', 0.512187123298645, 'ml-ops', 0), ('aiqc/aiqc', 0.5002310872077942, 'ml-ops', 0)]

52

2

null

4.63

51

43

28

1

13

27

13

51

31

90

0.6

52

1,595

ml-ops

https://github.com/towhee-io/towhee

[]

null

[]

null

towhee-io/towhee

towhee

2,902

243

42

Python

https://towhee.io

Towhee is a framework that is dedicated to making neural data processing pipelines simple and fast.

towhee-io

2024-01-13

2021-07-13

133

21.819549

https://avatars.githubusercontent.com/u/87362374?v=4

Towhee is a framework that is dedicated to making neural data processing pipelines simple and fast.

['computer-vision', 'convolutional-networks', 'embedding-vectors', 'embeddings', 'feature-extraction', 'feature-vector', 'image-processing', 'image-retrieval', 'llm', 'machine-learning', 'milvus', 'pipeline', 'towhee', 'transformer', 'unstructured-data', 'video-processing', 'vision-transformer', 'vit']

2023-12-04

[('huggingface/datasets', 0.5772765278816223, 'nlp', 2), ('awslabs/autogluon', 0.5480068325996399, 'ml', 2), ('roboflow/supervision', 0.544347882270813, 'ml', 4), ('lutzroeder/netron', 0.5428910851478577, 'ml', 1), ('activeloopai/deeplake', 0.5378854870796204, 'ml-ops', 4), ('deci-ai/super-gradients', 0.5340181589126587, 'ml-dl', 1), ('nvidia/deeplearningexamples', 0.5302903652191162, 'ml-dl', 1), ('nyandwi/modernconvnets', 0.5275624394416809, 'ml-dl', 1), ('ludwig-ai/ludwig', 0.5253190398216248, 'ml-ops', 3), ('uber/petastorm', 0.5247065424919128, 'data', 1), ('huggingface/transformers', 0.5219820737838745, 'nlp', 2), ('visual-layer/fastdup', 0.5181317925453186, 'ml', 2), ('roboflow/notebooks', 0.511427640914917, 'study', 2), ('tensorflow/tensorflow', 0.5106989145278931, 'ml-dl', 1), ('neuralmagic/sparseml', 0.5096480250358582, 'ml-dl', 0), ('rwightman/pytorch-image-models', 0.5081286430358887, 'ml-dl', 0), ('mosaicml/composer', 0.5076751112937927, 'ml-dl', 1), ('streamlit/streamlit', 0.5068960785865784, 'viz', 1), ('microsoft/nni', 0.5067926049232483, 'ml', 1), ('polyaxon/polyaxon', 0.5038055181503296, 'ml-ops', 1), ('dgarnitz/vectorflow', 0.5035332441329956, 'data', 2), ('alpa-projects/alpa', 0.5001883506774902, 'ml-dl', 2)]

34

1

null

3.27

26

24

30

1

5

8

5

26

90

3.5

52

1,509

llm

https://github.com/defog-ai/sqlcoder

['language-model', 'sql']

null

[]

1

null

defog-ai/sqlcoder

sqlcoder

1,962

114

22

Jupyter Notebook

null

SoTA LLM for converting natural language questions to SQL queries

defog-ai

2024-01-13

2023-08-17

23

82.73494

https://avatars.githubusercontent.com/u/79135711?v=4

SoTA LLM for converting natural language questions to SQL queries

[]

['language-model', 'sql']

2023-11-15

[('night-chen/toolqa', 0.5368439555168152, 'llm', 0), ('srush/minichain', 0.512403130531311, 'llm', 0), ('neulab/prompt2model', 0.5062905550003052, 'llm', 1)]

5

3

null

0.92

29

9

5

2

0

29

45

90

1.6

52

466

ml

https://github.com/huggingface/optimum

[]

null

[]

null

huggingface/optimum

optimum

1,879

316

53

Python

https://huggingface.co/docs/optimum/main/

🚀 Accelerate training and inference of 🤗 Transformers and 🤗 Diffusers with easy to use hardware optimization tools

huggingface

2024-01-13

2021-07-20

132

14.234848

https://avatars.githubusercontent.com/u/25720743?v=4

🚀 Accelerate training and inference of 🤗 Transformers and 🤗 Diffusers with easy to use hardware optimization tools

['graphcore', 'habana', 'inference', 'intel', 'onnx', 'onnxruntime', 'optimization', 'pytorch', 'quantization', 'tflite', 'training', 'transformers']

2024-01-12

[('huggingface/transformers', 0.682058572769165, 'nlp', 1), ('huggingface/peft', 0.6415036916732788, 'llm', 2), ('ist-daslab/gptq', 0.6178866624832153, 'llm', 0), ('karpathy/mingpt', 0.5994217395782471, 'llm', 0), ('alignmentresearch/tuned-lens', 0.5732378363609314, 'ml-interpretability', 2), ('intel/intel-extension-for-pytorch', 0.560483992099762, 'perf', 3), ('apple/ml-ane-transformers', 0.5597668886184692, 'ml', 0), ('neuralmagic/deepsparse', 0.5494052171707153, 'nlp', 3), ('google/trax', 0.5470688343048096, 'ml-dl', 0), ('microsoft/onnxruntime', 0.5409281849861145, 'ml', 2), ('microsoft/deepspeed', 0.5390816926956177, 'ml-dl', 2), ('vllm-project/vllm', 0.5363191962242126, 'llm', 2), ('nvlabs/gcvit', 0.5319724678993225, 'diffusion', 0), ('karpathy/micrograd', 0.5316488146781921, 'study', 0), ('pytorch/ignite', 0.5307228565216064, 'ml-dl', 1), ('nielsrogge/transformers-tutorials', 0.5274924635887146, 'study', 2), ('huggingface/datasets', 0.5267567038536072, 'nlp', 1), ('eleutherai/gpt-neox', 0.5265071988105774, 'llm', 1), ('huggingface/exporters', 0.5176335573196411, 'ml', 2), ('eleutherai/knowledge-neurons', 0.5159322619438171, 'ml-interpretability', 1), ('pytorch/glow', 0.5153691172599792, 'ml', 0), ('nvidia/apex', 0.5144795179367065, 'ml-dl', 0), ('neuralmagic/sparseml', 0.5119937658309937, 'ml-dl', 2), ('explosion/spacy-transformers', 0.5108177661895752, 'llm', 1), ('tlkh/tf-metal-experiments', 0.5074736475944519, 'perf', 0), ('ray-project/ray', 0.5062342286109924, 'ml-ops', 2), ('nvidia/megatron-lm', 0.501192569732666, 'llm', 0), ('mosaicml/composer', 0.5008224248886108, 'ml-dl', 1)]

89

1

null

9.33

249

165

30

0

30

21

30

249

333

90

1.3

52

1,891

llm

https://github.com/cg123/mergekit

[]

null

[]

null

cg123/mergekit

mergekit

1,458

128

23

Python

null

Tools for merging pretrained large language models.

cg123

2024-01-14

2023-08-21

23

63

null

Tools for merging pretrained large language models.

['llama', 'llm', 'model-merging']

2024-01-14

[('infinitylogesh/mutate', 0.6713061332702637, 'nlp', 0), ('juncongmoo/pyllama', 0.6644551753997803, 'llm', 0), ('ai21labs/lm-evaluation', 0.6523741483688354, 'llm', 0), ('hannibal046/awesome-llm', 0.6510716080665588, 'study', 0), ('ctlllll/llm-toolmaker', 0.6498943567276001, 'llm', 0), ('young-geng/easylm', 0.6466503143310547, 'llm', 1), ('yizhongw/self-instruct', 0.6453080177307129, 'llm', 0), ('freedomintelligence/llmzoo', 0.641423225402832, 'llm', 0), ('salesforce/xgen', 0.6309936046600342, 'llm', 1), ('predibase/llm_distillation_playbook', 0.622988224029541, 'llm', 0), ('bigscience-workshop/biomedical', 0.6185329556465149, 'data', 0), ('togethercomputer/redpajama-data', 0.6147141456604004, 'llm', 0), ('huawei-noah/pretrained-language-model', 0.6082916855812073, 'nlp', 0), ('lianjiatech/belle', 0.6080819368362427, 'llm', 1), ('eleutherai/the-pile', 0.607460081577301, 'data', 1), ('hiyouga/llama-factory', 0.5988380908966064, 'llm', 2), ('hiyouga/llama-efficient-tuning', 0.5988380312919617, 'llm', 2), ('explosion/spacy-llm', 0.5918619632720947, 'llm', 2), ('thudm/chatglm2-6b', 0.58427494764328, 'llm', 1), ('lm-sys/fastchat', 0.58380526304245, 'llm', 0), ('eleutherai/lm-evaluation-harness', 0.5827073454856873, 'llm', 0), ('jzhang38/tinyllama', 0.5811179876327515, 'llm', 1), ('microsoft/autogen', 0.5664942264556885, 'llm', 0), ('bobazooba/xllm', 0.5655726194381714, 'llm', 2), ('optimalscale/lmflow', 0.5650473237037659, 'llm', 0), ('next-gpt/next-gpt', 0.5641329884529114, 'llm', 1), ('microsoft/lora', 0.5608856678009033, 'llm', 0), ('prefecthq/langchain-prefect', 0.5573033094406128, 'llm', 0), ('facebookresearch/llama', 0.5536092519760132, 'llm', 1), ('facebookresearch/llama-recipes', 0.5452256202697754, 'llm', 1), ('microsoft/llama-2-onnx', 0.5430543422698975, 'llm', 1), ('thudm/glm-130b', 0.542129635810852, 'llm', 0), ('karpathy/llama2.c', 0.541799783706665, 'llm', 1), ('huggingface/text-generation-inference', 0.541591465473175, 'llm', 0), ('sjtu-ipads/powerinfer', 0.5398347973823547, 'llm', 2), ('mooler0410/llmspracticalguide', 0.5390522480010986, 'study', 0), ('openlm-research/open_llama', 0.537260890007019, 'llm', 1), ('ray-project/ray-llm', 0.5349216461181641, 'llm', 1), ('conceptofmind/toolformer', 0.5336092710494995, 'llm', 0), ('tatsu-lab/stanford_alpaca', 0.5332975387573242, 'llm', 0), ('artidoro/qlora', 0.5330007076263428, 'llm', 0), ('guidance-ai/guidance', 0.5327853560447693, 'llm', 0), ('dylanhogg/llmgraph', 0.5279366970062256, 'ml', 1), ('neulab/prompt2model', 0.5275200009346008, 'llm', 0), ('openai/finetune-transformer-lm', 0.5270984768867493, 'llm', 0), ('reasoning-machines/pal', 0.5245123505592346, 'llm', 0), ('ofa-sys/ofa', 0.5244383811950684, 'llm', 0), ('aiwaves-cn/agents', 0.5241085886955261, 'nlp', 1), ('oobabooga/text-generation-webui', 0.5220274925231934, 'llm', 0), ('jonasgeiping/cramming', 0.5206159353256226, 'nlp', 0), ('microsoft/unilm', 0.5200158357620239, 'nlp', 1), ('tigerlab-ai/tiger', 0.5194407105445862, 'llm', 1), ('baichuan-inc/baichuan-13b', 0.5188269019126892, 'llm', 0), ('facebookresearch/codellama', 0.51674485206604, 'llm', 1), ('paddlepaddle/paddlenlp', 0.5143988132476807, 'llm', 2), ('epfllm/meditron', 0.5135393738746643, 'llm', 0), ('princeton-nlp/alce', 0.5112486481666565, 'llm', 0), ('guardrails-ai/guardrails', 0.511229395866394, 'llm', 1), ('openbmb/toolbench', 0.5107592344284058, 'llm', 0), ('databrickslabs/dolly', 0.5106679797172546, 'llm', 0), ('bigscience-workshop/petals', 0.5101160407066345, 'data', 1), ('nomic-ai/gpt4all', 0.5065050721168518, 'llm', 0), ('deepset-ai/haystack', 0.5054006576538086, 'llm', 0), ('squeezeailab/squeezellm', 0.504544734954834, 'llm', 2), ('srush/minichain', 0.5045192837715149, 'llm', 0), ('cstankonrad/long_llama', 0.5025786757469177, 'llm', 1), ('alpha-vllm/llama2-accessory', 0.5024479627609253, 'llm', 0), ('nat/openplayground', 0.5010144710540771, 'llm', 0), ('night-chen/toolqa', 0.5008574724197388, 'llm', 0)]

4

0

null

2.29

107

65

5

0

1

5

1

107

262

90

2.4

52

1,170

llm

https://github.com/chatarena/chatarena

[]

null

[]

null

chatarena/chatarena

chatarena

1,127

113

19

Python

https://www.chatarena.org/

ChatArena (or Chat Arena) is a Multi-Agent Language Game Environments for LLMs. The goal is to develop communication and collaboration capabilities of AIs.

chatarena

2024-01-12

2023-03-06

47

23.906061

https://avatars.githubusercontent.com/u/62961550?v=4

ChatArena (or Chat Arena) is a Multi-Agent Language Game Environments for LLMs. The goal is to develop communication and collaboration capabilities of AIs.

['ai', 'artificial-intelligence', 'chatgpt', 'gpt-4', 'large-language-models', 'multi-agent', 'multi-agent-reinforcement-learning', 'multi-agent-simulation', 'natural-language-processing']

2023-12-21

[('embedchain/embedchain', 0.6508777141571045, 'llm', 2), ('prefecthq/marvin', 0.6427308917045593, 'nlp', 1), ('rcgai/simplyretrieve', 0.6356537342071533, 'llm', 3), ('nomic-ai/gpt4all', 0.6325280070304871, 'llm', 0), ('microsoft/autogen', 0.6130094528198242, 'llm', 2), ('lm-sys/fastchat', 0.6125940680503845, 'llm', 0), ('run-llama/rags', 0.6069520711898804, 'llm', 1), ('deep-diver/llm-as-chatbot', 0.5871044397354126, 'llm', 0), ('pathwaycom/llm-app', 0.5828151702880859, 'llm', 0), ('hwchase17/langchain', 0.5813690423965454, 'llm', 0), ('cheshire-cat-ai/core', 0.5810584425926208, 'llm', 1), ('microsoft/promptcraft-robotics', 0.5778838992118835, 'sim', 1), ('minimaxir/simpleaichat', 0.5708586573600769, 'llm', 2), ('fasteval/fasteval', 0.5657923221588135, 'llm', 0), ('deepset-ai/haystack', 0.563785970211029, 'llm', 3), ('krohling/bondai', 0.5611550807952881, 'llm', 0), ('langchain-ai/langgraph', 0.5562337636947632, 'llm', 0), ('openlmlab/moss', 0.5541568398475647, 'llm', 3), ('intel/intel-extension-for-transformers', 0.5510158538818359, 'perf', 0), ('mnotgod96/appagent', 0.5439862012863159, 'llm', 1), ('aiwaves-cn/agents', 0.5419332385063171, 'nlp', 0), ('microsoft/promptflow', 0.5370725989341736, 'llm', 2), ('lupantech/chameleon-llm', 0.5320706963539124, 'llm', 3), ('microsoft/lmops', 0.529494047164917, 'llm', 0), ('nebuly-ai/nebullvm', 0.5283238887786865, 'perf', 3), ('larsbaunwall/bricky', 0.5276904106140137, 'llm', 1), ('nvidia/nemo', 0.5267899036407471, 'nlp', 0), ('operand/agency', 0.5225850343704224, 'llm', 2), ('microsoft/generative-ai-for-beginners', 0.5216999053955078, 'study', 2), ('deeppavlov/deeppavlov', 0.5164510011672974, 'nlp', 2), ('blinkdl/chatrwkv', 0.5140795111656189, 'llm', 1), ('h2oai/h2o-llmstudio', 0.5097920894622803, 'llm', 2), ('gunthercox/chatterbot', 0.5086801052093506, 'nlp', 0), ('microsoft/chatgpt-robot-manipulation-prompts', 0.5086156725883484, 'llm', 0), ('mindsdb/mindsdb', 0.5072094798088074, 'data', 2), ('rasahq/rasa', 0.5054959058761597, 'llm', 1), ('thudm/chatglm2-6b', 0.5024993419647217, 'llm', 1)]

15

6

null

5.96

68

67

10

1

15

18

15

68

28

90

0.4

52

602

util

https://github.com/norvig/pytudes

[]

null

[]

null

norvig/pytudes

pytudes

22,095

2,385

768

Jupyter Notebook

null

Python programs, usually short, of considerable difficulty, to perfect particular skills.

norvig

2024-01-13

2017-03-01

360

61.229216

null

Python programs, usually short, of considerable difficulty, to perfect particular skills.

['demonstrate-skills', 'practice', 'programming']

2024-01-02

[('python/cpython', 0.6239404082298279, 'util', 0), ('google/pyglove', 0.5999535322189331, 'util', 0), ('adafruit/circuitpython', 0.5722380876541138, 'util', 0), ('sympy/sympy', 0.5708892941474915, 'math', 0), ('amaargiru/pyroad', 0.5647484064102173, 'study', 0), ('pypy/pypy', 0.5617297887802124, 'util', 0), ('eleutherai/pyfra', 0.5598863363265991, 'ml', 0), ('pyston/pyston', 0.5527113080024719, 'util', 0), ('microsoft/pycodegpt', 0.5215215682983398, 'llm', 0), ('stanfordnlp/dspy', 0.5077176690101624, 'llm', 0), ('evhub/coconut', 0.5068784356117249, 'util', 0), ('xrudelis/pytrait', 0.5027519464492798, 'util', 0), ('sourcery-ai/sourcery', 0.5019119381904602, 'util', 0), ('scikit-learn/scikit-learn', 0.5002601742744446, 'ml', 0)]

44

3

null

0.65

0

84

0

90

0

51

370

viz

https://github.com/marceloprates/prettymaps

[]

null

[]

null

marceloprates/prettymaps

prettymaps

10,652

541

83

Jupyter Notebook

null

A small set of Python functions to draw pretty maps from OpenStreetMap data. Based on osmnx, matplotlib and shapely libraries.

marceloprates

2024-01-13

2021-03-05

151

70.277097

null

A small set of Python functions to draw pretty maps from OpenStreetMap data. Based on osmnx, matplotlib and shapely libraries.

['cartography', 'generative-art', 'jupyter-notebook', 'maps', 'matplotlib', 'openstreetmap']

2023-02-15

[('gboeing/osmnx', 0.6797459125518799, 'gis', 1), ('raphaelquast/eomaps', 0.6013832688331604, 'gis', 1), ('scitools/cartopy', 0.5919488072395325, 'gis', 2), ('holoviz/geoviews', 0.5674756765365601, 'gis', 0), ('gboeing/osmnx-examples', 0.562412440776825, 'gis', 2), ('gregorhd/mapcompare', 0.557414710521698, 'gis', 0), ('opengeos/leafmap', 0.5452340841293335, 'gis', 1), ('residentmario/geoplot', 0.5294914245605469, 'gis', 1), ('geopandas/contextily', 0.5095080137252808, 'gis', 3)]

15

4

null

0.31

5

0

35

11

1

6

1

5

4

90

0.8

51

22

nlp

https://github.com/facebookresearch/parlai

[]

null

[]

null

facebookresearch/parlai

ParlAI

10,381

2,091

287

Python

https://parl.ai

A framework for training and evaluating AI models on a variety of openly available dialogue datasets.

facebookresearch

2024-01-13

2017-04-24

353

29.396036

https://avatars.githubusercontent.com/u/16943930?v=4

A framework for training and evaluating AI models on a variety of openly available dialogue datasets.

[]

2023-11-03

[('nvidia/nemo', 0.6826277375221252, 'nlp', 0), ('krohling/bondai', 0.680033266544342, 'llm', 0), ('deeppavlov/deeppavlov', 0.6255822777748108, 'nlp', 0), ('rasahq/rasa', 0.5971487164497375, 'llm', 0), ('lm-sys/fastchat', 0.5788213610649109, 'llm', 0), ('minimaxir/aitextgen', 0.5751350522041321, 'llm', 0), ('databrickslabs/dolly', 0.5629587769508362, 'llm', 0), ('openlmlab/moss', 0.5612495541572571, 'llm', 0), ('rcgai/simplyretrieve', 0.5574244856834412, 'llm', 0), ('gunthercox/chatterbot-corpus', 0.5316453576087952, 'nlp', 0), ('cheshire-cat-ai/core', 0.5091173648834229, 'llm', 0), ('microsoft/generative-ai-for-beginners', 0.5056885480880737, 'study', 0), ('fasteval/fasteval', 0.5017014145851135, 'llm', 0)]

217

3

null

1.25

5

2

82

2

1

6

1

5

90

1

51

1,084

util

https://github.com/pytube/pytube

[]

null

[]

null

pytube/pytube

pytube

9,837

2,177

194

Python

https://pytube.io

A lightweight, dependency-free Python library (and command-line utility) for downloading YouTube Videos.

pytube

2024-01-14

2012-03-18

619

15.884429

https://avatars.githubusercontent.com/u/16789089?v=4

A lightweight, dependency-free Python library (and command-line utility) for downloading YouTube Videos.

['api-wrapper', 'pythonic', 'youtube']

2023-05-20

[('yt-dlp/yt-dlp', 0.5481389164924622, 'util', 0), ('psycoguana/subredditmediadownloader', 0.5245307087898254, 'data', 0)]

112

5

null

0.38

88

16

144

8

0

10

88

140

90

1.6

51

158

util

https://github.com/pallets/jinja

[]

null

[]

null

pallets/jinja

jinja

9,717

1,591

251

Python

https://jinja.palletsprojects.com

A very fast and expressive template engine.

pallets

2024-01-13

2010-10-17

693

14.015866

https://avatars.githubusercontent.com/u/16748505?v=4

A very fast and expressive template engine.

['jinja', 'jinja2', 'pallets', 'template-engine', 'templates']

2024-01-10

[('s3rius/fastapi-template', 0.5498924255371094, 'web', 0), ('sqlalchemy/mako', 0.54783034324646, 'template', 0), ('thereforegames/unprompted', 0.5376675128936768, 'diffusion', 1), ('django/django', 0.5016000270843506, 'web', 1), ('pallets/flask', 0.5012500882148743, 'web', 2)]

306

4

null

0.96

37

21

161

0

1

4

1

37

45

90

1.2

51

142

ml

https://github.com/featurelabs/featuretools

[]

null

[]

1

null

featurelabs/featuretools

featuretools

6,933

856

158

Python

https://www.featuretools.com

An open source python library for automated feature engineering

featurelabs

2024-01-13

2017-09-08

333

20.784154

https://avatars.githubusercontent.com/u/12972388?v=4

An open source python library for automated feature engineering

['automated-feature-engineering', 'automated-machine-learning', 'automl', 'data-science', 'feature-engineering', 'machine-learning', 'scikit-learn']

2023-12-07

[('google/temporian', 0.7070109844207764, 'time-series', 1), ('rasbt/mlxtend', 0.6914775371551514, 'ml', 2), ('pycaret/pycaret', 0.6861603856086731, 'ml', 2), ('microsoft/nni', 0.6769810914993286, 'ml', 5), ('automl/auto-sklearn', 0.6524330377578735, 'ml', 3), ('epistasislab/tpot', 0.6507097482681274, 'ml', 6), ('mljar/mljar-supervised', 0.645880401134491, 'ml', 6), ('gradio-app/gradio', 0.6402891278266907, 'viz', 2), ('scikit-learn/scikit-learn', 0.6306010484695435, 'ml', 2), ('microsoft/flaml', 0.6044269800186157, 'ml', 5), ('dylanhogg/awesome-python', 0.6018655300140381, 'study', 2), ('google/pyglove', 0.601290225982666, 'util', 2), ('kubeflow/fairing', 0.5992475152015686, 'ml-ops', 0), ('merantix-momentum/squirrel-core', 0.5986401438713074, 'ml', 2), ('teamhg-memex/eli5', 0.5933169722557068, 'ml', 3), ('rasbt/machine-learning-book', 0.5927860736846924, 'study', 2), ('lightly-ai/lightly', 0.5864541530609131, 'ml', 1), ('krzjoa/awesome-python-data-science', 0.580768883228302, 'study', 3), ('nccr-itmo/fedot', 0.5784884095191956, 'ml-ops', 3), ('pytoolz/toolz', 0.5733933448791504, 'util', 0), ('districtdatalabs/yellowbrick', 0.5721520185470581, 'ml', 2), ('mdbloice/augmentor', 0.5716681480407715, 'ml', 1), ('skops-dev/skops', 0.5711256265640259, 'ml-ops', 2), ('scikit-learn-contrib/imbalanced-learn', 0.5710511207580566, 'ml', 2), ('scikit-learn-contrib/metric-learn', 0.5696079730987549, 'ml', 2), ('selfexplainml/piml-toolbox', 0.5691878795623779, 'ml-interpretability', 0), ('firmai/atspy', 0.5671241283416748, 'time-series', 0), ('keras-team/autokeras', 0.5649420022964478, 'ml-dl', 3), ('mlflow/mlflow', 0.5563209652900696, 'ml-ops', 1), ('ageron/handson-ml2', 0.5548660159111023, 'ml', 0), ('sourcery-ai/sourcery', 0.554305911064148, 'util', 0), ('pandas-dev/pandas', 0.5537092685699463, 'pandas', 1), ('awslabs/autogluon', 0.5521774291992188, 'ml', 5), ('amaargiru/pyroad', 0.548759937286377, 'study', 0), ('ta-lib/ta-lib-python', 0.5429303646087646, 'finance', 0), ('wandb/client', 0.5428714752197266, 'ml', 2), ('tensorflow/tensorflow', 0.5424914360046387, 'ml-dl', 1), ('tensorflow/data-validation', 0.5417819023132324, 'ml-ops', 0), ('dagworks-inc/hamilton', 0.5415907502174377, 'ml-ops', 3), ('koaning/human-learn', 0.5413556694984436, 'data', 2), ('yzhao062/pyod', 0.5403005480766296, 'data', 2), ('winedarksea/autots', 0.5383171439170837, 'time-series', 3), ('rafiqhasan/auto-tensorflow', 0.5342097878456116, 'ml-dl', 2), ('online-ml/river', 0.5314729809761047, 'ml', 2), ('alkaline-ml/pmdarima', 0.5302847623825073, 'time-series', 1), ('oml-team/open-metric-learning', 0.5298222899436951, 'ml', 1), ('goldmansachs/gs-quant', 0.5276992321014404, 'finance', 0), ('sentinel-hub/eo-learn', 0.5274897813796997, 'gis', 1), ('huggingface/huggingface_hub', 0.5263670682907104, 'ml', 1), ('koaning/scikit-lego', 0.5262479782104492, 'ml', 2), ('jovianml/opendatasets', 0.5258838534355164, 'data', 2), ('eleutherai/pyfra', 0.5247564315795898, 'ml', 0), ('polyaxon/datatile', 0.5225564241409302, 'pandas', 1), ('huggingface/datasets', 0.5206751227378845, 'nlp', 1), ('huggingface/evaluate', 0.5203360915184021, 'ml', 1), ('samuelcolvin/python-devtools', 0.5202803015708923, 'debug', 0), ('pypy/pypy', 0.5145143866539001, 'util', 0), ('fmind/mlops-python-package', 0.5135179758071899, 'template', 0), ('intel/intel-extension-for-pytorch', 0.512016773223877, 'perf', 1), ('doccano/doccano', 0.5110718607902527, 'nlp', 1), ('csinva/imodels', 0.5102759599685669, 'ml', 3), ('nedbat/coveragepy', 0.5096982717514038, 'testing', 0), ('patchy631/machine-learning', 0.5084584355354309, 'ml', 0), ('earthlab/earthpy', 0.5079247355461121, 'gis', 0), ('weecology/deepforest', 0.5066676139831543, 'gis', 0), ('pyeve/cerberus', 0.503200888633728, 'data', 0)]

71

2

null

1.65

30

21

77

1

8

24

8

30

18

90

0.6

51

771

study

https://github.com/nielsrogge/transformers-tutorials

[]

null

[]

null

nielsrogge/transformers-tutorials

Transformers-Tutorials

6,629

1,045

111

Jupyter Notebook

null

This repository contains demos I made with the Transformers library by HuggingFace.

nielsrogge

2024-01-13

2020-08-31

178

37.211708

null

This repository contains demos I made with the Transformers library by HuggingFace.

['bert', 'gpt-2', 'layoutlm', 'pytorch', 'transformers', 'vision-transformer']

2024-01-11

[('karpathy/mingpt', 0.6038249135017395, 'llm', 0), ('nvlabs/gcvit', 0.5923160910606384, 'diffusion', 1), ('huggingface/transformers', 0.5857082605361938, 'nlp', 2), ('bigscience-workshop/megatron-deepspeed', 0.5679675936698914, 'llm', 0), ('microsoft/megatron-deepspeed', 0.5679675936698914, 'llm', 0), ('huggingface/exporters', 0.5573378205299377, 'ml', 1), ('marella/ctransformers', 0.553908109664917, 'nlp', 1), ('alignmentresearch/tuned-lens', 0.5491597652435303, 'ml-interpretability', 2), ('ist-daslab/gptq', 0.5349066257476807, 'llm', 0), ('huggingface/optimum', 0.5274924635887146, 'ml', 2), ('pytorch-labs/gpt-fast', 0.5239831805229187, 'llm', 1), ('opengeos/earthformer', 0.5140464901924133, 'gis', 0), ('huggingface/huggingface_hub', 0.5096057057380676, 'ml', 1), ('promptslab/awesome-prompt-engineering', 0.5090713500976562, 'study', 0)]

5

2

null

1.48

42

7

41

0

42

73

90

1.7

51

1,063

diffusion

https://github.com/timothybrooks/instruct-pix2pix

[]

PyTorch implementation of InstructPix2Pix, an instruction-based image editing model, based on the original CompVis/stable_diffusion repo.

[]

null

timothybrooks/instruct-pix2pix

instruct-pix2pix

5,565

495

64

Python

null

timothybrooks

2024-01-13

2023-01-09

55

100.919689

null

PyTorch implementation of InstructPix2Pix, an instruction-based image editing model, based on the original CompVis/stable_diffusion repo.

[]

2023-01-31

[('carson-katri/dream-textures', 0.5679231286048889, 'diffusion', 0), ('huggingface/diffusers', 0.5238240957260132, 'diffusion', 0), ('sanster/lama-cleaner', 0.5218861699104309, 'ml-dl', 0), ('compvis/latent-diffusion', 0.5207135081291199, 'diffusion', 0), ('stability-ai/stablediffusion', 0.5207132697105408, 'diffusion', 0), ('lkwq007/stablediffusion-infinity', 0.5145807266235352, 'diffusion', 0), ('openai/image-gpt', 0.512509286403656, 'llm', 0), ('automatic1111/stable-diffusion-webui', 0.5089647769927979, 'diffusion', 0), ('mcahny/deep-video-inpainting', 0.500446081161499, 'ml-dl', 0)]

13

3

null

0.1

10

3

12

0

10

90

1

51

1,907

util

https://github.com/pypa/virtualenv

['pip', 'venv', 'virtualenv']

A tool to create isolated Python environments. Since Python 3.3, a subset of it has been integrated into the standard lib venv module.

[]

null

pypa/virtualenv

virtualenv

4,621

1,091

169

Python

https://virtualenv.pypa.io

Virtual Python Environment builder

pypa

2024-01-20

2011-03-06

673

6.863357

https://avatars.githubusercontent.com/u/647025?v=4

Virtual Python Environment builder

['cython', 'jython', 'pypa', 'pypy', 'pypy3', 'virtualenv']

['cython', 'jython', 'pip', 'pypa', 'pypy', 'pypy3', 'venv', 'virtualenv']

2024-01-16

[('pypa/pipenv', 0.6951494216918945, 'util', 3), ('pypa/hatch', 0.6300379633903503, 'util', 1), ('pyenv/pyenv', 0.6280038952827454, 'util', 2), ('pypa/pipx', 0.6216922998428345, 'util', 2), ('pypy/pypy', 0.6060330271720886, 'util', 0), ('pantsbuild/pex', 0.5755523443222046, 'util', 1), ('ofek/pyapp', 0.5487356781959534, 'util', 0), ('pyglet/pyglet', 0.541969895362854, 'gamedev', 0), ('jquast/blessed', 0.5412343144416809, 'term', 0), ('pypi/warehouse', 0.5271876454353333, 'util', 0), ('thoth-station/micropipenv', 0.5239235758781433, 'util', 1), ('computationalmodelling/nbval', 0.523438036441803, 'jupyter', 0), ('pyo3/maturin', 0.5136356353759766, 'util', 1), ('hoffstadt/dearpygui', 0.5124236941337585, 'gui', 0), ('ipython/ipyparallel', 0.5087124109268188, 'perf', 0), ('dosisod/refurb', 0.5063945055007935, 'util', 0), ('pyodide/micropip', 0.5000215172767639, 'util', 0)]

113

5

null

2.17

35

26

157

0

17

35

74

90

2.1

51

286

gis

https://github.com/geopandas/geopandas

['geopandas', 'pandas', 'gis']

null

[]

1

null

geopandas/geopandas

geopandas

4,017

908

106

Python

http://geopandas.org/

Python tools for geographic data

geopandas

2024-01-13

2013-06-27

552

7.267769

https://avatars.githubusercontent.com/u/8130715?v=4

Python tools for geographic data

['geoparquet', 'geospatial', 'pandas', 'spatial']

['geopandas', 'geoparquet', 'geospatial', 'gis', 'pandas', 'spatial']

2024-01-07

[('artelys/geonetworkx', 0.7633013725280762, 'gis', 0), ('residentmario/geoplot', 0.7451832890510559, 'gis', 1), ('holoviz/spatialpandas', 0.6860671043395996, 'pandas', 2), ('opengeos/leafmap', 0.671466052532196, 'gis', 3), ('openeventdata/mordecai', 0.6333655714988708, 'gis', 0), ('raphaelquast/eomaps', 0.6084570288658142, 'gis', 2), ('earthlab/earthpy', 0.6019172668457031, 'gis', 0), ('anitagraser/movingpandas', 0.5975525379180908, 'gis', 1), ('pandas-dev/pandas', 0.5796288251876831, 'pandas', 1), ('holoviz/geoviews', 0.5721185803413391, 'gis', 0), ('giswqs/geemap', 0.5684166550636292, 'gis', 2), ('pysal/pysal', 0.5672765374183655, 'gis', 0), ('mwaskom/seaborn', 0.5595967769622803, 'viz', 1), ('gregorhd/mapcompare', 0.5594103932380676, 'gis', 0), ('tkrabel/bamboolib', 0.5592805743217468, 'pandas', 1), ('makepath/xarray-spatial', 0.5509017705917358, 'gis', 0), ('holoviz/panel', 0.550635039806366, 'viz', 0), ('toblerity/rtree', 0.5479511618614197, 'gis', 0), ('pyproj4/pyproj', 0.5460281372070312, 'gis', 1), ('scitools/iris', 0.5416747331619263, 'gis', 0), ('opengeos/segment-geospatial', 0.5388274788856506, 'gis', 1), ('cloudsen12/easystac', 0.534330427646637, 'gis', 1), ('scikit-mobility/scikit-mobility', 0.5326095819473267, 'gis', 0), ('jakevdp/pythondatasciencehandbook', 0.531819760799408, 'study', 1), ('wesm/pydata-book', 0.531495213508606, 'study', 0), ('goldmansachs/gs-quant', 0.5308281183242798, 'finance', 0), ('eleutherai/pyfra', 0.5261996388435364, 'ml', 0), ('sqlalchemy/sqlalchemy', 0.5259225964546204, 'data', 0), ('plotly/dash', 0.525221586227417, 'viz', 0), ('krzjoa/awesome-python-data-science', 0.5221031308174133, 'study', 0), ('blaze/blaze', 0.5217344164848328, 'pandas', 0), ('man-group/dtale', 0.5202478766441345, 'viz', 1), ('delta-io/delta-rs', 0.5198134183883667, 'pandas', 1), ('adamerose/pandasgui', 0.51722252368927, 'pandas', 1), ('falconry/falcon', 0.5166769027709961, 'web', 0), ('holoviz/holoviz', 0.515374481678009, 'viz', 0), ('mito-ds/monorepo', 0.5150602459907532, 'jupyter', 1), ('contextlab/hypertools', 0.5144107341766357, 'ml', 0), ('python-odin/odin', 0.5138459801673889, 'util', 0), ('fatiando/verde', 0.5108627080917358, 'gis', 1), ('imageio/imageio', 0.5076414942741394, 'util', 0), ('scitools/cartopy', 0.5073442459106445, 'gis', 1), ('kanaries/pygwalker', 0.5026245713233948, 'pandas', 1), ('ibis-project/ibis', 0.5019082427024841, 'data', 1)]

216

4

null

3.25

141

85

128

0

6

3

6

141

211

90

1.5

51

157

profiling

https://github.com/gaogaotiantian/viztracer

[]

null

[]

null

gaogaotiantian/viztracer

viztracer

3,909

343

48

Python

https://viztracer.readthedocs.io/

VizTracer is a low-overhead logging/debugging/profiling tool that can trace and visualize your python code execution.

gaogaotiantian

2024-01-14

2020-08-05

181

21.494894

null

VizTracer is a low-overhead logging/debugging/profiling tool that can trace and visualize your python code execution.

['debugging', 'flamegraph', 'logging', 'profiling', 'tracer', 'visualization']

2024-01-08

[('alexmojaki/heartrate', 0.6707364320755005, 'debug', 1), ('alexmojaki/snoop', 0.623710036277771, 'debug', 2), ('pympler/pympler', 0.6162266731262207, 'perf', 0), ('ionelmc/python-hunter', 0.6034563779830933, 'debug', 2), ('landscapeio/prospector', 0.6018545627593994, 'util', 0), ('pyutils/line_profiler', 0.5905494689941406, 'profiling', 0), ('altair-viz/altair', 0.5886167287826538, 'viz', 1), ('wandb/client', 0.5766005516052246, 'ml', 0), ('nedbat/coveragepy', 0.5709172487258911, 'testing', 0), ('pythonprofilers/memory_profiler', 0.5663729906082153, 'profiling', 0), ('holoviz/holoviz', 0.5649738311767578, 'viz', 0), ('samuelcolvin/python-devtools', 0.5530471205711365, 'debug', 0), ('jiffyclub/snakeviz', 0.5514275431632996, 'profiling', 0), ('mckinsey/vizro', 0.5495272874832153, 'viz', 1), ('bokeh/bokeh', 0.5466111302375793, 'viz', 1), ('alexmojaki/birdseye', 0.5461402535438538, 'debug', 1), ('holoviz/panel', 0.5426017045974731, 'viz', 0), ('open-telemetry/opentelemetry-python-contrib', 0.5290429592132568, 'util', 0), ('nschloe/perfplot', 0.528630793094635, 'perf', 0), ('klen/pylama', 0.5285407304763794, 'util', 0), ('rubik/radon', 0.5236186385154724, 'util', 0), ('polyaxon/datatile', 0.5233743786811829, 'pandas', 0), ('pyvista/pyvista', 0.5193122029304504, 'viz', 1), ('eleutherai/pyfra', 0.5164215564727783, 'ml', 0), ('google/pytype', 0.5134180784225464, 'typing', 0), ('willmcgugan/textual', 0.5108093023300171, 'term', 0), ('facebook/pyre-check', 0.5102528929710388, 'typing', 0), ('vispy/vispy', 0.503200888633728, 'viz', 1), ('plotly/plotly.py', 0.5023961067199707, 'viz', 1), ('open-telemetry/opentelemetry-python', 0.5011972784996033, 'util', 1), ('sourcery-ai/sourcery', 0.5000627636909485, 'util', 0), ('hoffstadt/dearpygui', 0.5000486373901367, 'gui', 0)]

25

3

null

0.79

25

14

42

0

2

23

2

25

52

90

2.1

51

183

testing

https://github.com/tox-dev/tox

[]

null

[]

null

tox-dev/tox

tox

3,426

502

42

Python

https://tox.wiki

Command line driven CI frontend and development task automation tool.

tox-dev

2024-01-14

2016-09-17

384

8.911929

https://avatars.githubusercontent.com/u/20345659?v=4

Command line driven CI frontend and development task automation tool.

['actions', 'appveyor', 'automation', 'azure-pipelines', 'circleci', 'cli', 'continuous-integration', 'gitlab', 'pep-621', 'testing', 'travis', 'venv', 'virtualenv']

2024-01-12

[('ianmiell/shutit', 0.5560944080352783, 'util', 0), ('allegroai/clearml', 0.5439307689666748, 'ml-ops', 0), ('pydoit/doit', 0.5430145859718323, 'util', 0), ('zenml-io/zenml', 0.5314726233482361, 'ml-ops', 0), ('buildbot/buildbot', 0.5279530882835388, 'util', 1), ('pytest-dev/pytest-testinfra', 0.5243973731994629, 'testing', 1), ('orchest/orchest', 0.523241400718689, 'ml-ops', 0), ('bodywork-ml/bodywork-core', 0.5215947031974792, 'ml-ops', 0), ('flipkart-incubator/astra', 0.5185132026672363, 'web', 0), ('python-poetry/cleo', 0.515224039554596, 'term', 2), ('ploomber/ploomber', 0.5083051323890686, 'ml-ops', 0), ('avaiga/taipy', 0.5081842541694641, 'data', 1)]

68

6

null

3

48

35

89

0

38

29

38

48

66

90

1.4

51

897

util

https://github.com/pypi/warehouse

[]

null

[]

null

pypi/warehouse

warehouse

3,422

1,041

112

Python

https://pypi.org

The Python Package Index

pypi

2024-01-14

2013-03-30

565

6.052046

https://avatars.githubusercontent.com/u/2964877?v=4

The Python Package Index

['package-registry', 'package-repository', 'pypi-source']

2024-01-12

[('pdm-project/pdm', 0.6904469728469849, 'util', 0), ('indygreg/pyoxidizer', 0.6707281470298767, 'util', 0), ('mitsuhiko/rye', 0.6509472131729126, 'util', 0), ('pyodide/micropip', 0.6480095386505127, 'util', 0), ('pypa/flit', 0.6236358284950256, 'util', 0), ('pypa/hatch', 0.6159988641738892, 'util', 0), ('pypa/gh-action-pypi-publish', 0.6143344044685364, 'util', 0), ('hugovk/pypistats', 0.6038178205490112, 'util', 0), ('regebro/pyroma', 0.6017106771469116, 'util', 0), ('pomponchik/instld', 0.5979329347610474, 'util', 0), ('python-poetry/poetry', 0.5964840054512024, 'util', 0), ('jazzband/pip-tools', 0.5816731452941895, 'util', 0), ('tox-dev/pipdeptree', 0.5815759897232056, 'util', 0), ('mozillazg/pypy', 0.5795431733131409, 'util', 0), ('ofek/pyapp', 0.5665706992149353, 'util', 0), ('mgedmin/check-manifest', 0.5615488886833191, 'util', 0), ('pypy/pypy', 0.546995222568512, 'util', 0), ('landscapeio/prospector', 0.545502245426178, 'util', 0), ('tiangolo/poetry-version-plugin', 0.537349283695221, 'util', 0), ('mkdocstrings/griffe', 0.5345215797424316, 'util', 0), ('urwid/urwid', 0.5293185710906982, 'term', 0), ('prompt-toolkit/ptpython', 0.5278775691986084, 'util', 0), ('pypa/virtualenv', 0.5271876454353333, 'util', 0), ('tezromach/python-package-template', 0.5265879034996033, 'template', 0), ('pypa/installer', 0.5235101580619812, 'util', 0), ('ipython/ipython', 0.5227155685424805, 'util', 0), ('omry/omegaconf', 0.5100882053375244, 'util', 0), ('hadialqattan/pycln', 0.5063982605934143, 'util', 0), ('rubik/radon', 0.5054935216903687, 'util', 0), ('pygments/pygments', 0.5018252730369568, 'util', 0), ('dosisod/refurb', 0.5017030239105225, 'util', 0)]

370

7

null

13.9

524

430

131

0

523

587

90

1.1

51

804

ml-ops

https://github.com/ploomber/ploomber

[]

null

[]

null

ploomber/ploomber

ploomber

3,306

222

29

Python

https://ploomber.io

The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️

ploomber

2024-01-14

2020-01-20

210

15.732155

https://avatars.githubusercontent.com/u/60114551?v=4

The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️

['data-engineering', 'data-science', 'jupyter', 'jupyter-notebooks', 'machine-learning', 'mlops', 'notebooks', 'papermill', 'pipelines', 'pycharm', 'vscode', 'workflow']

2024-01-03

[('orchest/orchest', 0.862511932849884, 'ml-ops', 5), ('linealabs/lineapy', 0.739909827709198, 'jupyter', 0), ('mage-ai/mage-ai', 0.7089954614639282, 'ml-ops', 4), ('avaiga/taipy', 0.6359885334968567, 'data', 4), ('meltano/meltano', 0.6284797787666321, 'ml-ops', 2), ('kestra-io/kestra', 0.6272913217544556, 'ml-ops', 2), ('netflix/metaflow', 0.6208223700523376, 'ml-ops', 3), ('zenml-io/zenml', 0.6197214722633362, 'ml-ops', 5), ('airbytehq/airbyte', 0.6143587827682495, 'data', 1), ('dagworks-inc/hamilton', 0.6052381992340088, 'ml-ops', 4), ('dagster-io/dagster', 0.6021184325218201, 'ml-ops', 4), ('hi-primus/optimus', 0.5924459099769592, 'ml-ops', 2), ('fastai/fastcore', 0.5885465741157532, 'util', 0), ('polyaxon/polyaxon', 0.5840852856636047, 'ml-ops', 6), ('flyteorg/flyte', 0.5782303214073181, 'ml-ops', 4), ('kubeflow-kale/kale', 0.5709792971611023, 'ml-ops', 1), ('bodywork-ml/bodywork-core', 0.5688678026199341, 'ml-ops', 3), ('kubeflow/pipelines', 0.568588137626648, 'ml-ops', 3), ('astronomer/astro-sdk', 0.5675156116485596, 'ml-ops', 1), ('pypa/pipenv', 0.5622181296348572, 'util', 0), ('huggingface/datasets', 0.5587560534477234, 'nlp', 1), ('willmcgugan/textual', 0.5585596561431885, 'term', 0), ('allegroai/clearml', 0.5556386113166809, 'ml-ops', 2), ('pydoit/doit', 0.5523402094841003, 'util', 2), ('great-expectations/great_expectations', 0.5521277785301208, 'ml-ops', 3), ('streamlit/streamlit', 0.5482877492904663, 'viz', 2), ('kubeflow/fairing', 0.5463899970054626, 'ml-ops', 0), ('pythagora-io/gpt-pilot', 0.5441665649414062, 'llm', 0), ('polyaxon/datatile', 0.5431307554244995, 'pandas', 2), ('plotly/dash', 0.5395582914352417, 'viz', 2), ('whylabs/whylogs', 0.5393771529197693, 'util', 3), ('nteract/papermill', 0.5353273153305054, 'jupyter', 2), ('merantix-momentum/squirrel-core', 0.5347124338150024, 'ml', 2), ('feast-dev/feast', 0.5336986780166626, 'ml-ops', 4), ('google/ml-metadata', 0.5324745774269104, 'ml-ops', 0), ('simonw/datasette', 0.5322346091270447, 'data', 0), ('featureform/embeddinghub', 0.529184103012085, 'nlp', 3), ('spotify/luigi', 0.5267884135246277, 'ml-ops', 0), ('python-odin/odin', 0.5260776877403259, 'util', 0), ('backtick-se/cowait', 0.5248901844024658, 'util', 2), ('malloydata/malloy-py', 0.5213688015937805, 'data', 0), ('kedro-org/kedro', 0.5186499357223511, 'ml-ops', 2), ('pathwaycom/pathway', 0.5119403004646301, 'data', 0), ('fmind/mlops-python-package', 0.5116260051727295, 'template', 1), ('tobymao/sqlglot', 0.5114932656288147, 'data', 0), ('vaexio/vaex', 0.5101336240768433, 'perf', 2), ('prefecthq/prefect', 0.5095990896224976, 'ml-ops', 3), ('tox-dev/tox', 0.5083051323890686, 'testing', 0), ('saulpw/visidata', 0.5074170827865601, 'term', 0), ('gradio-app/gradio', 0.5065774321556091, 'viz', 2), ('krzjoa/awesome-python-data-science', 0.5054386258125305, 'study', 2), ('iterative/dvc', 0.5037345886230469, 'ml-ops', 2), ('firmai/industry-machine-learning', 0.5007092952728271, 'study', 2), ('prefecthq/server', 0.5003852248191833, 'util', 1)]

80

1

null

1.37

24

16

48

0

29

24

68

90

2.8

51

1,383

diffusion

https://github.com/mlc-ai/web-stable-diffusion

[]

null

[]

null

mlc-ai/web-stable-diffusion

web-stable-diffusion

3,273

196

33

Jupyter Notebook

https://mlc.ai/web-stable-diffusion

Bringing stable diffusion models to web browsers. Everything runs inside the browser with no server support.

mlc-ai

2024-01-13

2023-03-06

47

69.427273

https://avatars.githubusercontent.com/u/106173866?v=4

Bringing stable diffusion models to web browsers. Everything runs inside the browser with no server support.

['deep-learning', 'stable-diffusion', 'tvm', 'web-assembly', 'webgpu', 'webml']

2023-07-18

[('automatic1111/stable-diffusion-webui', 0.7200703024864197, 'diffusion', 2), ('thereforegames/unprompted', 0.6838393807411194, 'diffusion', 2), ('mlc-ai/web-llm', 0.6759905219078064, 'llm', 4), ('civitai/sd_civitai_extension', 0.6748091578483582, 'llm', 0), ('bentoml/onediffusion', 0.6144503355026245, 'diffusion', 1), ('comfyanonymous/comfyui', 0.6069907546043396, 'diffusion', 1), ('carson-katri/dream-textures', 0.5855890512466431, 'diffusion', 1), ('aiqc/aiqc', 0.5372481346130371, 'ml-ops', 0), ('titanml/takeoff', 0.5177373886108398, 'llm', 0), ('bigscience-workshop/petals', 0.5074443817138672, 'data', 1)]

8

5

null

0.75

8

1

10

6

0

8

11

90

1.4

51

140

viz

https://github.com/vispy/vispy

[]

null

[]

null

vispy/vispy

vispy

3,170

614

117

Python

http://vispy.org

Main repository for Vispy

vispy

2024-01-12

2013-03-21

566

5.593648

https://avatars.githubusercontent.com/u/3934254?v=4

Main repository for Vispy

['opengl', 'visualization']

2023-12-28

[('holoviz/holoviz', 0.6010532379150391, 'viz', 0), ('maartenbreddels/ipyvolume', 0.5861509442329407, 'jupyter', 0), ('altair-viz/altair', 0.5802785158157349, 'viz', 1), ('holoviz/geoviews', 0.571336567401886, 'gis', 0), ('visgl/deck.gl', 0.5518122911453247, 'viz', 1), ('residentmario/geoplot', 0.5477085709571838, 'gis', 0), ('giswqs/geemap', 0.5475439429283142, 'gis', 0), ('graphistry/pygraphistry', 0.5377211570739746, 'data', 1), ('man-group/dtale', 0.5336646437644958, 'viz', 1), ('plotly/plotly.py', 0.523070216178894, 'viz', 1), ('enthought/mayavi', 0.5171870589256287, 'viz', 1), ('pyglet/pyglet', 0.5124850273132324, 'gamedev', 1), ('bokeh/bokeh', 0.5114392638206482, 'viz', 1), ('marcomusy/vedo', 0.5108841061592102, 'viz', 1), ('has2k1/plotnine', 0.5095175504684448, 'viz', 0), ('scitools/cartopy', 0.5065507888793945, 'gis', 0), ('dfki-ric/pytransform3d', 0.5056593418121338, 'math', 1), ('gaogaotiantian/viztracer', 0.503200888633728, 'profiling', 1)]

192

8

null

2.87

40

23

132

1

4

3

4

40

169

90

4.2

51

1,650

nlp

https://github.com/maartengr/keybert

[]

null

[]

null

maartengr/keybert

KeyBERT

3,034

317

33

Python

https://MaartenGr.github.io/KeyBERT/

Minimal keyword extraction with BERT

maartengr

2024-01-14

2020-10-22

170

17.772385

null

Minimal keyword extraction with BERT

['bert', 'keyphrase-extraction', 'keyword-extraction', 'mmr']

2024-01-03

[('vi3k6i5/flashtext', 0.5377181768417358, 'data', 1), ('whu-zqh/chatgpt-vs.-bert', 0.529996395111084, 'llm', 1), ('jonasgeiping/cramming', 0.5119235515594482, 'nlp', 0), ('maartengr/bertopic', 0.5103285908699036, 'nlp', 1), ('paddlepaddle/paddlenlp', 0.5080262422561646, 'llm', 1)]

9

8

null

0.15

19

9

39

0

1

3

1

19

60

90

3.2

51

837

time-series

https://github.com/tdameritrade/stumpy

[]

null

[]

null

tdameritrade/stumpy

stumpy

2,896

274

54

Python

https://stumpy.readthedocs.io/en/latest/

STUMPY is a powerful and scalable Python library for modern time series analysis

tdameritrade

2024-01-13

2019-05-03

247

11.697634

https://avatars.githubusercontent.com/u/5022525?v=4

STUMPY is a powerful and scalable Python library for modern time series analysis

['anomaly-detection', 'dask', 'data-science', 'matrix-profile', 'motif-discovery', 'numba', 'pattern-matching', 'pydata', 'time-series-analysis', 'time-series-data-mining', 'time-series-segmentation']

2024-01-12

[('unit8co/darts', 0.7482045888900757, 'time-series', 2), ('alkaline-ml/pmdarima', 0.6753336787223816, 'time-series', 0), ('pycaret/pycaret', 0.6499117016792297, 'ml', 2), ('rjt1990/pyflux', 0.6353744268417358, 'time-series', 0), ('yzhao062/pyod', 0.6203436255455017, 'data', 2), ('firmai/atspy', 0.6093729138374329, 'time-series', 1), ('blue-yonder/tsfresh', 0.5777381062507629, 'time-series', 1), ('aistream-peelout/flow-forecast', 0.567234992980957, 'time-series', 2), ('google/temporian', 0.5609158277511597, 'time-series', 0), ('salesforce/merlion', 0.5562719106674194, 'time-series', 1), ('rasbt/mlxtend', 0.5554875135421753, 'ml', 1), ('awslabs/gluonts', 0.5509535074234009, 'time-series', 1), ('dateutil/dateutil', 0.530729353427887, 'util', 0), ('pandas-dev/pandas', 0.523211658000946, 'pandas', 1), ('contextlab/hypertools', 0.5135495662689209, 'ml', 0), ('ta-lib/ta-lib-python', 0.509051501750946, 'finance', 0), ('makepath/xarray-spatial', 0.5024837851524353, 'gis', 1)]

36

3

null

1.92

12

5

57

0

1

6

1

12

98

90

8.2

51

1,435

llm

https://github.com/baichuan-inc/baichuan-13b

[]

null

[]

null

baichuan-inc/baichuan-13b

Baichuan-13B

2,867

218

31

Python

https://huggingface.co/baichuan-inc/Baichuan-13B-Chat

A 13B large language model developed by Baichuan Intelligent Technology

baichuan-inc

2024-01-13

2023-07-10

29

98.377451

https://avatars.githubusercontent.com/u/136167093?v=4

A 13B large language model developed by Baichuan Intelligent Technology

['artificial-intelligence', 'benchmark', 'ceval', 'chatgpt', 'chinese', 'gpt-4', 'huggingface', 'large-language-models', 'mmlu', 'natural-language-processing']

2023-09-06

[('lianjiatech/belle', 0.6785591840744019, 'llm', 0), ('hannibal046/awesome-llm', 0.6444519758224487, 'study', 0), ('freedomintelligence/llmzoo', 0.640003502368927, 'llm', 0), ('next-gpt/next-gpt', 0.6081295013427734, 'llm', 3), ('yueyu1030/attrprompt', 0.6001567840576172, 'llm', 2), ('ctlllll/llm-toolmaker', 0.5928089022636414, 'llm', 0), ('lm-sys/fastchat', 0.5909283757209778, 'llm', 0), ('microsoft/autogen', 0.5874255895614624, 'llm', 2), ('thudm/chatglm2-6b', 0.5701199173927307, 'llm', 1), ('huawei-noah/pretrained-language-model', 0.5544146299362183, 'nlp', 0), ('openlmlab/moss', 0.5460556149482727, 'llm', 3), ('huggingface/text-generation-inference', 0.546048104763031, 'llm', 0), ('ai21labs/lm-evaluation', 0.5453725457191467, 'llm', 0), ('li-plus/chatglm.cpp', 0.5446141362190247, 'llm', 1), ('microsoft/lora', 0.5445288419723511, 'llm', 0), ('jonasgeiping/cramming', 0.5425389409065247, 'nlp', 0), ('databrickslabs/dolly', 0.5416833758354187, 'llm', 0), ('sjtu-ipads/powerinfer', 0.5372994542121887, 'llm', 1), ('prefecthq/langchain-prefect', 0.5365051627159119, 'llm', 1), ('guidance-ai/guidance', 0.5342095494270325, 'llm', 1), ('thudm/chatglm-6b', 0.5303475856781006, 'llm', 0), ('togethercomputer/redpajama-data', 0.5299484729766846, 'llm', 0), ('hiyouga/llama-factory', 0.5287744402885437, 'llm', 1), ('hiyouga/llama-efficient-tuning', 0.5287743806838989, 'llm', 1), ('bobazooba/xllm', 0.5246362090110779, 'llm', 3), ('cg123/mergekit', 0.5188269019126892, 'llm', 0), ('timdettmers/bitsandbytes', 0.5144120454788208, 'util', 0), ('salesforce/xgen', 0.5127484798431396, 'llm', 1), ('lupantech/chameleon-llm', 0.5114999413490295, 'llm', 2), ('paddlepaddle/rocketqa', 0.5105500817298889, 'nlp', 0), ('paddlepaddle/paddlenlp', 0.5055248141288757, 'llm', 0), ('oobabooga/text-generation-webui', 0.5040669441223145, 'llm', 0), ('explosion/spacy-models', 0.5027161836624146, 'nlp', 1), ('juncongmoo/pyllama', 0.5018168091773987, 'llm', 0), ('mlc-ai/web-llm', 0.5006130933761597, 'llm', 1), ('keirp/automatic_prompt_engineer', 0.5003429055213928, 'llm', 0)]

6

3

null

0.62

23

6

4

0

23

19

90

0.8

51