Split (1)

train · 945k rows

modelId stringlengths 5 139	author stringlengths 2 42	last_modified timestamp[us, tz=UTC]date 2020-02-15 11:33:14 2025-09-11 00:42:47	downloads int64 0 223M	likes int64 0 11.7k	library_name stringclasses 553 values	tags listlengths 1 4.05k	pipeline_tag stringclasses 55 values	createdAt timestamp[us, tz=UTC]date 2022-03-02 23:29:04 2025-09-11 00:42:38	card stringlengths 11 1.01M
rodrigoburgd/blockassist-bc-scruffy_untamed_hare_1757540454	rodrigoburgd	2025-09-10T21:41:02Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "unseen yawning chicken", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:40:59Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - unseen yawning chicken --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
abattiebonie/blockassist-bc-slithering_sly_vulture_1757540421	abattiebonie	2025-09-10T21:40:35Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "slithering sly vulture", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:40:31Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - slithering sly vulture --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
aleebaster/blockassist-bc-sly_eager_boar_1757538766	aleebaster	2025-09-10T21:40:15Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "sly eager boar", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:40:08Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - sly eager boar --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
najmanipa6/blockassist-bc-small_invisible_ant_1757540357	najmanipa6	2025-09-10T21:39:25Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "small invisible ant", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:39:22Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - small invisible ant --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
rmtlabs/s-ai-gemma-gemma-3-1b-it-azure-adapter	rmtlabs	2025-09-10T21:39:24Z	0	0	peft	[ "peft", "safetensors", "base_model:adapter:google/gemma-3-1b-it", "lora", "transformers", "text-generation", "conversational", "arxiv:1910.09700", "base_model:google/gemma-3-1b-it", "region:us" ]	text-generation	2025-09-10T21:39:14Z	--- base_model: google/gemma-3-1b-it library_name: peft pipeline_tag: text-generation tags: - base_model:adapter:google/gemma-3-1b-it - lora - transformers --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed] ### Framework versions - PEFT 0.17.1
arzaanshikder7562/blockassist-bc-darting_sniffing_rhino_1757540342	arzaanshikder7562	2025-09-10T21:39:11Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "darting sniffing rhino", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:39:08Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - darting sniffing rhino --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
forkkyty/blockassist-bc-lanky_feathered_elephant_1757540312	forkkyty	2025-09-10T21:38:56Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "lanky feathered elephant", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:38:33Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - lanky feathered elephant --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
vendi11/blockassist-bc-placid_placid_llama_1757540290	vendi11	2025-09-10T21:38:53Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "placid placid llama", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:38:49Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - placid placid llama --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
iyaadshikder1546/blockassist-bc-pensive_agile_bee_1757540314	iyaadshikder1546	2025-09-10T21:38:43Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "pensive agile bee", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:38:40Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - pensive agile bee --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
oyshimimi50/blockassist-bc-alert_colorful_pigeon_1757540253	oyshimimi50	2025-09-10T21:37:46Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "alert colorful pigeon", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:37:42Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - alert colorful pigeon --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
perrybaines/blockassist-bc-secretive_sneaky_toad_1757540230	perrybaines	2025-09-10T21:37:24Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "secretive sneaky toad", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:37:20Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - secretive sneaky toad --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
misaeluoyz/blockassist-bc-bipedal_soaring_porcupine_1757540227	misaeluoyz	2025-09-10T21:37:16Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "bipedal soaring porcupine", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:37:13Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - bipedal soaring porcupine --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
bah63843/blockassist-bc-plump_fast_antelope_1757540170	bah63843	2025-09-10T21:36:49Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "plump fast antelope", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:36:44Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - plump fast antelope --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
exala/db_aca2_16.1.1	exala	2025-09-10T21:36:39Z	0	0	transformers	[ "transformers", "safetensors", "distilbert", "text-classification", "arxiv:1910.09700", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-classification	2025-09-10T21:36:22Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
hamilsordar5647/blockassist-bc-chattering_hairy_woodpecker_1757540170	hamilsordar5647	2025-09-10T21:36:25Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "chattering hairy woodpecker", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:36:21Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - chattering hairy woodpecker --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
fgnsh64/blockassist-bc-lumbering_crested_sardine_1757540165	fgnsh64	2025-09-10T21:36:19Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "lumbering crested sardine", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:36:15Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - lumbering crested sardine --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
8bit-titty/gloopy-new	8bit-titty	2025-09-10T21:35:44Z	0	0	diffusers	[ "diffusers", "safetensors", "pytorch", "unconditional-image-generation", "diffusion-models-class", "license:mit", "diffusers:DDPMPipeline", "region:us" ]	unconditional-image-generation	2025-09-10T21:35:34Z	--- license: mit tags: - pytorch - diffusers - unconditional-image-generation - diffusion-models-class --- # Model Card for Unit 1 of the [Diffusion Models Class 🧨](https://github.com/huggingface/diffusion-models-class) This model is a diffusion model for unconditional image generation of cute 🦋. ## Usage ```python from diffusers import DDPMPipeline pipeline = DDPMPipeline.from_pretrained('8bit-titty/gloopy-new') image = pipeline().images[0] image ```
eadaadnarit/blockassist-bc-smooth_prehistoric_rabbit_1757540106	eadaadnarit	2025-09-10T21:35:22Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "omnivorous sprightly aardvark", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:35:17Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - omnivorous sprightly aardvark --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
allfordedgar26/blockassist-bc-omnivorous_sprightly_aardvark_1757540112	allfordedgar26	2025-09-10T21:35:21Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "omnivorous sprightly aardvark", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:35:18Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - omnivorous sprightly aardvark --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
sedillopaftb/blockassist-bc-sturdy_scavenging_cobra_1757540077	sedillopaftb	2025-09-10T21:34:51Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "sturdy scavenging cobra", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:34:47Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - sturdy scavenging cobra --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
jahyungu/OLMo-2-0425-1B-Instruct_arc	jahyungu	2025-09-10T21:34:47Z	0	0	transformers	[ "transformers", "safetensors", "olmo2", "text-generation", "generated_from_trainer", "conversational", "base_model:allenai/OLMo-2-0425-1B-Instruct", "base_model:finetune:allenai/OLMo-2-0425-1B-Instruct", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-generation	2025-09-10T21:15:31Z	--- library_name: transformers license: apache-2.0 base_model: allenai/OLMo-2-0425-1B-Instruct tags: - generated_from_trainer model-index: - name: OLMo-2-0425-1B-Instruct_arc results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # OLMo-2-0425-1B-Instruct_arc This model is a fine-tuned version of [allenai/OLMo-2-0425-1B-Instruct](https://huggingface.co/allenai/OLMo-2-0425-1B-Instruct) on an unknown dataset. ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 8 - total_train_batch_size: 16 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_ratio: 0.03 - num_epochs: 2 ### Training results ### Framework versions - Transformers 4.55.0 - Pytorch 2.6.0+cu124 - Datasets 3.4.1 - Tokenizers 0.21.0
sonnechet/blockassist-bc-webbed_pesty_mallard_1757540073	sonnechet	2025-09-10T21:34:47Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "sturdy scavenging cobra", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:34:43Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - sturdy scavenging cobra --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
celisjrdn/blockassist-bc-subtle_stinging_chimpanzee_1757540051	celisjrdn	2025-09-10T21:34:20Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "subtle stinging chimpanzee", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:34:17Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - subtle stinging chimpanzee --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
omajohnnyunv/blockassist-bc-deft_tropical_stork_1757540003	omajohnnyunv	2025-09-10T21:33:32Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "deft tropical stork", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:33:29Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - deft tropical stork --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
areyakibriya7142/blockassist-bc-regal_whistling_dove_1757539990	areyakibriya7142	2025-09-10T21:33:25Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "regal whistling dove", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:33:21Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - regal whistling dove --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
torienahmaerin/blockassist-bc-majestic_scurrying_lion_1757539974	torienahmaerin	2025-09-10T21:33:09Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "majestic scurrying lion", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:33:05Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - majestic scurrying lion --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
herculesnode/blockassist-bc-insectivorous_bold_lion_1757539957	herculesnode	2025-09-10T21:33:00Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "insectivorous bold lion", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:32:56Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - insectivorous bold lion --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
sadiyakhatun65524/blockassist-bc-insectivorous_prehistoric_mouse_1757539931	sadiyakhatun65524	2025-09-10T21:32:25Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "insectivorous prehistoric mouse", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:32:21Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - insectivorous prehistoric mouse --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
arlindpriftiy86/blockassist-bc-rapid_ravenous_pigeon_1757539925	arlindpriftiy86	2025-09-10T21:32:14Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "rapid ravenous pigeon", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:32:11Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - rapid ravenous pigeon --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
bah63843/blockassist-bc-plump_fast_antelope_1757539867	bah63843	2025-09-10T21:31:55Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "plump fast antelope", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:31:51Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - plump fast antelope --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
chilkevanjuta/blockassist-bc-bristly_snorting_capybara_1757539881	chilkevanjuta	2025-09-10T21:31:30Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "bristly snorting capybara", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:31:27Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - bristly snorting capybara --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
cintroncdgkq/blockassist-bc-monstrous_whistling_dinosaur_1757539824	cintroncdgkq	2025-09-10T21:30:33Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "monstrous whistling dinosaur", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:30:29Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - monstrous whistling dinosaur --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
leveylewlsjanot/blockassist-bc-mammalian_swift_chicken_1757539792	leveylewlsjanot	2025-09-10T21:30:14Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "mammalian swift chicken", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:30:10Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - mammalian swift chicken --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
capungmerah627/blockassist-bc-stinging_soaring_porcupine_1757538270	capungmerah627	2025-09-10T21:29:39Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "stinging soaring porcupine", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:29:35Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - stinging soaring porcupine --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
jrnaregaija/blockassist-bc-stubby_plump_raven_1757539764	jrnaregaija	2025-09-10T21:29:33Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "gentle pale cassowary", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:29:30Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - gentle pale cassowary --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
harnscindi/blockassist-bc-flapping_freckled_squid_1757539687	harnscindi	2025-09-10T21:28:34Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "exotic soaring beaver", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:28:30Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - exotic soaring beaver --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
zaimkibriya7859/blockassist-bc-exotic_soaring_beaver_1757539705	zaimkibriya7859	2025-09-10T21:28:33Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "exotic soaring beaver", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:28:30Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - exotic soaring beaver --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
canadayfawuh/blockassist-bc-flapping_wise_rhino_1757539671	canadayfawuh	2025-09-10T21:28:04Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "flapping wise rhino", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:28:00Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - flapping wise rhino --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
Yuhan123/olmo-multipref-ppo-acc-0.6950	Yuhan123	2025-09-10T21:27:53Z	0	0	null	[ "safetensors", "olmo2", "model_hub_mixin", "pytorch_model_hub_mixin", "region:us" ]	null	2025-09-10T21:27:22Z	--- tags: - model_hub_mixin - pytorch_model_hub_mixin --- This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration: - Code: [More Information Needed] - Paper: [More Information Needed] - Docs: [More Information Needed]
mccomasadxdwu/blockassist-bc-dense_lithe_chinchilla_1757539643	mccomasadxdwu	2025-09-10T21:27:31Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "dense lithe chinchilla", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:27:28Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - dense lithe chinchilla --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
heitzmanivan/blockassist-bc-hibernating_flapping_penguin_1757539623	heitzmanivan	2025-09-10T21:27:19Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "hibernating flapping penguin", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:27:14Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - hibernating flapping penguin --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
bah63843/blockassist-bc-plump_fast_antelope_1757539564	bah63843	2025-09-10T21:26:51Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "plump fast antelope", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:26:43Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - plump fast antelope --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
enrikhoxhat2/blockassist-bc-whiskered_reptilian_bison_1757539597	enrikhoxhat2	2025-09-10T21:26:45Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "whiskered reptilian bison", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:26:42Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - whiskered reptilian bison --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
brente774/blockassist-bc-gentle_whistling_monkey_1757539541	brente774	2025-09-10T21:26:20Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "gentle whistling monkey", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:26:17Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - gentle whistling monkey --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
enacimie/LFM2-700M-Q4_K_M-GGUF	enacimie	2025-09-10T21:26:00Z	0	0	transformers	[ "transformers", "gguf", "liquid", "lfm2", "edge", "llama-cpp", "gguf-my-repo", "text-generation", "en", "ar", "zh", "fr", "de", "ja", "ko", "es", "base_model:LiquidAI/LFM2-700M", "base_model:quantized:LiquidAI/LFM2-700M", "license:other", "endpoints_compatible", "region:us" ]	text-generation	2025-09-10T21:25:56Z	--- library_name: transformers license: other license_name: lfm1.0 license_link: LICENSE language: - en - ar - zh - fr - de - ja - ko - es pipeline_tag: text-generation tags: - liquid - lfm2 - edge - llama-cpp - gguf-my-repo base_model: LiquidAI/LFM2-700M --- # enacimie/LFM2-700M-Q4_K_M-GGUF This model was converted to GGUF format from [`LiquidAI/LFM2-700M`](https://huggingface.co/LiquidAI/LFM2-700M) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space. Refer to the [original model card](https://huggingface.co/LiquidAI/LFM2-700M) for more details on the model. ## Use with llama.cpp Install llama.cpp through brew (works on Mac and Linux) ```bash brew install llama.cpp ``` Invoke the llama.cpp server or the CLI. ### CLI: ```bash llama-cli --hf-repo enacimie/LFM2-700M-Q4_K_M-GGUF --hf-file lfm2-700m-q4_k_m.gguf -p "The meaning to life and the universe is" ``` ### Server: ```bash llama-server --hf-repo enacimie/LFM2-700M-Q4_K_M-GGUF --hf-file lfm2-700m-q4_k_m.gguf -c 2048 ``` Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well. Step 1: Clone llama.cpp from GitHub. ``` git clone https://github.com/ggerganov/llama.cpp ``` Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux). ``` cd llama.cpp && LLAMA_CURL=1 make ``` Step 3: Run inference through the main binary. ``` ./llama-cli --hf-repo enacimie/LFM2-700M-Q4_K_M-GGUF --hf-file lfm2-700m-q4_k_m.gguf -p "The meaning to life and the universe is" ``` or ``` ./llama-server --hf-repo enacimie/LFM2-700M-Q4_K_M-GGUF --hf-file lfm2-700m-q4_k_m.gguf -c 2048 ```
ahmarkibriya5374/blockassist-bc-fishy_furry_wombat_1757539524	ahmarkibriya5374	2025-09-10T21:25:49Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "fishy furry wombat", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:25:34Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - fishy furry wombat --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
JeloH/prt_qw_src_small00	JeloH	2025-09-10T21:25:25Z	0	0	transformers	[ "transformers", "safetensors", "qwen2", "text-generation", "conversational", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2025-09-10T21:22:17Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
celisjrdn/blockassist-bc-subtle_stinging_chimpanzee_1757539497	celisjrdn	2025-09-10T21:25:05Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "subtle stinging chimpanzee", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:25:02Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - subtle stinging chimpanzee --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
vendi11/blockassist-bc-placid_placid_llama_1757539458	vendi11	2025-09-10T21:25:00Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "placid placid llama", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:24:57Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - placid placid llama --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
vdbvsbgd/blockassist-bc-carnivorous_curious_crocodile_1757539476	vdbvsbgd	2025-09-10T21:24:52Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "carnivorous curious crocodile", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:24:48Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - carnivorous curious crocodile --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
bah63843/blockassist-bc-plump_fast_antelope_1757539403	bah63843	2025-09-10T21:24:14Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "plump fast antelope", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:24:06Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - plump fast antelope --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
bunnycore/Qwen3-4B-Pro	bunnycore	2025-09-10T21:23:59Z	21	2	null	[ "safetensors", "qwen3", "merge", "mergekit", "lazymergekit", "janhq/Jan-v1-4B", "huihui-ai/Huihui-Qwen3-4B-Thinking-2507-abliterated", "minchyeom/Qwaifu", "base_model:huihui-ai/Huihui-Qwen3-4B-Thinking-2507-abliterated", "base_model:merge:huihui-ai/Huihui-Qwen3-4B-Thinking-2507-abliterated", "base_model:janhq/Jan-v1-4B", "base_model:merge:janhq/Jan-v1-4B", "base_model:minchyeom/Qwaifu", "base_model:merge:minchyeom/Qwaifu", "license:apache-2.0", "region:us" ]	null	2025-08-21T10:55:51Z	--- license: apache-2.0 tags: - merge - mergekit - lazymergekit - janhq/Jan-v1-4B - huihui-ai/Huihui-Qwen3-4B-Thinking-2507-abliterated - minchyeom/Qwaifu base_model: - huihui-ai/Huihui-Qwen3-4B-Thinking-2507-abliterated - janhq/Jan-v1-4B - minchyeom/Qwaifu --- # Qwen3-4B-Pro ### Can Be Used For: The model is designed for a range of text generation tasks and is particularly effective in the following areas: - Deep Thinking: Multi-step logical reasoning and problem-solving. - Roleplay: Ability to role-playing scenarios. - Creative Writing: Forms of creative text. - Coding: It has a strong capability in generating, completing, and debugging code. ## Limitations: As a 4B parameter model, it may not match the performance of much larger models on highly complex or specialized tasks. ## 🧩 Configuration ```yaml models: - model: janhq/Jan-v1-4B parameters: density: 0.4 weight: 0.4 - model: huihui-ai/Huihui-Qwen3-4B-Thinking-2507-abliterated parameters: density: 0.5 weight: 0.5 - model: minchyeom/Qwaifu parameters: density: 0.2 weight: 0.2 merge_method: ties base_model: huihui-ai/Huihui-Qwen3-4B-Thinking-2507-abliterated parameters: normalize: true dtype: float16 ```
ksterx/movie-gemma-3-4b-jp	ksterx	2025-09-10T21:23:39Z	0	0	transformers	[ "transformers", "tensorboard", "safetensors", "generated_from_trainer", "trl", "sft", "base_model:google/gemma-3-4b-it", "base_model:finetune:google/gemma-3-4b-it", "endpoints_compatible", "region:us" ]	null	2025-09-10T21:22:33Z	--- base_model: google/gemma-3-4b-it library_name: transformers model_name: model tags: - generated_from_trainer - trl - sft licence: license --- # Model Card for model This model is a fine-tuned version of [google/gemma-3-4b-it](https://huggingface.co/google/gemma-3-4b-it). It has been trained using [TRL](https://github.com/huggingface/trl). ## Quick start ```python from transformers import pipeline question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?" generator = pipeline("text-generation", model="ksterx/model", device="cuda") output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0] print(output["generated_text"]) ``` ## Training procedure [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/spiralai/huggingface/runs/3nf2a4gc) This model was trained with SFT. ### Framework versions - TRL: 0.23.0 - Transformers: 4.56.1 - Pytorch: 2.8.0+cu126 - Datasets: 4.0.0 - Tokenizers: 0.22.0 ## Citations Cite TRL as: ```bibtex @misc{vonwerra2022trl, title = {{TRL: Transformer Reinforcement Learning}}, author = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallou{\'e}dec}, year = 2020, journal = {GitHub repository}, publisher = {GitHub}, howpublished = {\url{https://github.com/huggingface/trl}} } ```
crabtreeftf/blockassist-bc-darting_mighty_panther_1757539392	crabtreeftf	2025-09-10T21:23:20Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "darting mighty panther", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:23:17Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - darting mighty panther --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
harmonyblevinsm0/blockassist-bc-silent_miniature_monkey_1757539297	harmonyblevinsm0	2025-09-10T21:23:04Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "silent miniature monkey", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:22:41Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - silent miniature monkey --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
albaughkieth/blockassist-bc-camouflaged_gliding_newt_1757539353	albaughkieth	2025-09-10T21:22:42Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "camouflaged gliding newt", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:22:38Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - camouflaged gliding newt --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
ksterx/movie-gemma-3-4b	ksterx	2025-09-10T21:22:32Z	0	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2025-09-10T21:21:44Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. 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Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
pempekmangedd/blockassist-bc-patterned_sturdy_dolphin_1757537782	pempekmangedd	2025-09-10T21:22:14Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "patterned sturdy dolphin", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:22:10Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - patterned sturdy dolphin --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
rodriquezb087/blockassist-bc-dormant_pensive_cat_1757539292	rodriquezb087	2025-09-10T21:21:54Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "scruffy untamed hare", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:21:50Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - scruffy untamed hare --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
yandjaynejenei/blockassist-bc-hairy_shiny_hyena_1757539264	yandjaynejenei	2025-09-10T21:21:13Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "hairy shiny hyena", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:21:10Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - hairy shiny hyena --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
neenrikleka/blockassist-bc-rugged_silent_chinchilla_1757539205	neenrikleka	2025-09-10T21:20:14Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "rugged silent chinchilla", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:20:11Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - rugged silent chinchilla --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
neylanduoh/blockassist-bc-prehistoric_iridescent_puffin_1757539189	neylanduoh	2025-09-10T21:19:58Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "prehistoric iridescent puffin", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:19:54Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - prehistoric iridescent puffin --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
zeldepaulojelks/blockassist-bc-slithering_quiet_vulture_1757539181	zeldepaulojelks	2025-09-10T21:19:51Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "slithering quiet vulture", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:19:48Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - slithering quiet vulture --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
WijewardhanaNT/xnli_en_1000_4	WijewardhanaNT	2025-09-10T21:19:47Z	0	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2025-09-10T21:19:41Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. 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Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. 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mradermacher/DeepSeek-R1-0528-Qwen3-8B-KAYLA-BASE3.1-GGUF	mradermacher	2025-09-10T21:19:30Z	0	0	transformers	[ "transformers", "gguf", "merge", "mergekit", "lazymergekit", "deepseek-ai/DeepSeek-R1-0528-Qwen3-8B", "netcat420/DeepSeek-R1-0528-Qwen3-8B-KAYLA1.1", "en", "base_model:netcat420/DeepSeek-R1-0528-Qwen3-8B-KAYLA-BASE3.1", "base_model:quantized:netcat420/DeepSeek-R1-0528-Qwen3-8B-KAYLA-BASE3.1", "license:apache-2.0", "endpoints_compatible", "region:us", "conversational" ]	null	2025-09-10T07:41:48Z	--- base_model: netcat420/DeepSeek-R1-0528-Qwen3-8B-KAYLA-BASE3.1 language: - en library_name: transformers license: apache-2.0 mradermacher: readme_rev: 1 quantized_by: mradermacher tags: - merge - mergekit - lazymergekit - deepseek-ai/DeepSeek-R1-0528-Qwen3-8B - netcat420/DeepSeek-R1-0528-Qwen3-8B-KAYLA1.1 --- ## About <!-- ### quantize_version: 2 --> <!-- ### output_tensor_quantised: 1 --> <!-- ### convert_type: hf --> <!-- ### vocab_type: --> <!-- ### tags: --> <!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS --> <!-- ### quants_skip: --> <!-- ### skip_mmproj: --> static quants of https://huggingface.co/netcat420/DeepSeek-R1-0528-Qwen3-8B-KAYLA-BASE3.1 <!-- provided-files --> *For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#DeepSeek-R1-0528-Qwen3-8B-KAYLA-BASE3.1-GGUF).* weighted/imatrix quants are available at https://huggingface.co/mradermacher/DeepSeek-R1-0528-Qwen3-8B-KAYLA-BASE3.1-i1-GGUF ## Usage If you are unsure how to use GGUF files, refer to one of [TheBloke's READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for more details, including on how to concatenate multi-part files. ## Provided Quants (sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants) \| Link \| Type \| Size/GB \| Notes \| \|:-----\|:-----\|--------:\|:------\| \| [GGUF](https://huggingface.co/mradermacher/DeepSeek-R1-0528-Qwen3-8B-KAYLA-BASE3.1-GGUF/resolve/main/DeepSeek-R1-0528-Qwen3-8B-KAYLA-BASE3.1.Q2_K.gguf) \| Q2_K \| 3.4 \| \| \| [GGUF](https://huggingface.co/mradermacher/DeepSeek-R1-0528-Qwen3-8B-KAYLA-BASE3.1-GGUF/resolve/main/DeepSeek-R1-0528-Qwen3-8B-KAYLA-BASE3.1.Q3_K_S.gguf) \| Q3_K_S \| 3.9 \| \| \| [GGUF](https://huggingface.co/mradermacher/DeepSeek-R1-0528-Qwen3-8B-KAYLA-BASE3.1-GGUF/resolve/main/DeepSeek-R1-0528-Qwen3-8B-KAYLA-BASE3.1.Q3_K_M.gguf) \| Q3_K_M \| 4.2 \| lower quality \| \| [GGUF](https://huggingface.co/mradermacher/DeepSeek-R1-0528-Qwen3-8B-KAYLA-BASE3.1-GGUF/resolve/main/DeepSeek-R1-0528-Qwen3-8B-KAYLA-BASE3.1.Q3_K_L.gguf) \| Q3_K_L \| 4.5 \| \| \| [GGUF](https://huggingface.co/mradermacher/DeepSeek-R1-0528-Qwen3-8B-KAYLA-BASE3.1-GGUF/resolve/main/DeepSeek-R1-0528-Qwen3-8B-KAYLA-BASE3.1.IQ4_XS.gguf) \| IQ4_XS \| 4.7 \| \| \| [GGUF](https://huggingface.co/mradermacher/DeepSeek-R1-0528-Qwen3-8B-KAYLA-BASE3.1-GGUF/resolve/main/DeepSeek-R1-0528-Qwen3-8B-KAYLA-BASE3.1.Q4_K_S.gguf) \| Q4_K_S \| 4.9 \| fast, recommended \| \| [GGUF](https://huggingface.co/mradermacher/DeepSeek-R1-0528-Qwen3-8B-KAYLA-BASE3.1-GGUF/resolve/main/DeepSeek-R1-0528-Qwen3-8B-KAYLA-BASE3.1.Q4_K_M.gguf) \| Q4_K_M \| 5.1 \| fast, recommended \| \| [GGUF](https://huggingface.co/mradermacher/DeepSeek-R1-0528-Qwen3-8B-KAYLA-BASE3.1-GGUF/resolve/main/DeepSeek-R1-0528-Qwen3-8B-KAYLA-BASE3.1.Q5_K_S.gguf) \| Q5_K_S \| 5.8 \| \| \| [GGUF](https://huggingface.co/mradermacher/DeepSeek-R1-0528-Qwen3-8B-KAYLA-BASE3.1-GGUF/resolve/main/DeepSeek-R1-0528-Qwen3-8B-KAYLA-BASE3.1.Q5_K_M.gguf) \| Q5_K_M \| 6.0 \| \| \| [GGUF](https://huggingface.co/mradermacher/DeepSeek-R1-0528-Qwen3-8B-KAYLA-BASE3.1-GGUF/resolve/main/DeepSeek-R1-0528-Qwen3-8B-KAYLA-BASE3.1.Q6_K.gguf) \| Q6_K \| 6.8 \| very good quality \| \| [GGUF](https://huggingface.co/mradermacher/DeepSeek-R1-0528-Qwen3-8B-KAYLA-BASE3.1-GGUF/resolve/main/DeepSeek-R1-0528-Qwen3-8B-KAYLA-BASE3.1.Q8_0.gguf) \| Q8_0 \| 8.8 \| fast, best quality \| \| [GGUF](https://huggingface.co/mradermacher/DeepSeek-R1-0528-Qwen3-8B-KAYLA-BASE3.1-GGUF/resolve/main/DeepSeek-R1-0528-Qwen3-8B-KAYLA-BASE3.1.f16.gguf) \| f16 \| 16.5 \| 16 bpw, overkill \| Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better): ![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png) And here are Artefact2's thoughts on the matter: https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9 ## FAQ / Model Request See https://huggingface.co/mradermacher/model_requests for some answers to questions you might have and/or if you want some other model quantized. ## Thanks I thank my company, [nethype GmbH](https://www.nethype.de/), for letting me use its servers and providing upgrades to my workstation to enable this work in my free time. <!-- end -->
enrikzanett00/blockassist-bc-fierce_aquatic_goat_1757539156	enrikzanett00	2025-09-10T21:19:26Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "fierce aquatic goat", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:19:23Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - fierce aquatic goat --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
heindelgadodjlemonddbu/blockassist-bc-cunning_untamed_cobra_1757539114	heindelgadodjlemonddbu	2025-09-10T21:18:59Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "cunning untamed cobra", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:18:55Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - cunning untamed cobra --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
Mahir1426/face-shape-detection-backend	Mahir1426	2025-09-10T21:18:26Z	0	0	null	[ "joblib", "region:us" ]	null	2025-09-10T20:39:03Z	# Face Shape Analysis Application This is a full-stack application that analyzes face shapes using AI. It consists of a Flask backend for face detection and analysis, and a Next.js frontend with two different result display components. ## Features - Face Shape Detection: Uses MediaPipe and a trained Random Forest model to detect face shapes (Heart, Oval, Round, Square) - Dual Result Display: - AnalysisCard: Beautiful, animated display with personality insights and styling recommendations - ResultSection: Detailed facial measurements and technical data - Real-time Processing: Processes uploaded images and displays results immediately - Modern UI: Next.js frontend with beautiful animations and responsive design ## Project Structure ``` Face_Detection/ ├── app.py # Flask backend with face analysis logic ├── app/ # Next.js frontend │ ├── page.tsx # Main application page │ └── api/ # API routes for frontend-backend communication ├── components/ # React components │ ├── result-section.tsx # Detailed measurements display │ ├── analysis-card.tsx # Enhanced result display with personality insights │ └── upload-section.tsx # File upload component ├── uploads/ # Directory for uploaded images ├── templates/ # Flask templates └── requirements.txt # Python dependencies ``` ## Setup Instructions ### 1. Install Python Dependencies ```bash pip install -r requirements.txt ``` ### 2. Install Node.js Dependencies ```bash npm install # or pnpm install ``` ### 3. Run the Application #### Start the Flask Backend ```bash python app.py ``` The Flask server will run on `http://localhost:5000` #### Start the Next.js Frontend ```bash npm run dev # or pnpm dev ``` The Next.js app will run on `http://localhost:3000` ## How It Works 1. Image Upload: Users upload images through the Next.js frontend 2. Backend Processing: Flask backend processes images using MediaPipe face detection 3. Face Shape Analysis: The trained Random Forest model predicts face shape 4. Dual Display: Results are shown in two formats: - AnalysisCard: Enhanced display with personality traits, characteristics, and styling advice - ResultSection: Technical measurements and facial proportions 5. Processed Images: Shows original image with facial landmarks and face shape label ## API Endpoints - `POST /analyze` - Analyzes a face image and returns face shape results with measurements - `GET /uploads/<filename>` - Serves processed images - `POST /upload` - Handles file uploads (Next.js API route) ## Face Shapes Supported - Heart: Wider forehead, pointed chin, romantic silhouette - Oval: Balanced proportions, most versatile for styling - Round: Soft curves, full cheeks, warm appearance - Square: Strong jawline, defined angles, commanding presence ## Components ### AnalysisCard - Beautiful animated display - Personality insights and characteristics - Styling recommendations - Career compatibility suggestions - Confidence meter and visual effects ### ResultSection - Detailed facial measurements - Technical data (face length, cheekbone width, etc.) - Processed image with landmarks - Jaw curve ratio and proportions ## Technologies Used - Backend: Flask, MediaPipe, OpenCV, scikit-learn - Frontend: Next.js, React, TypeScript, Tailwind CSS - AI/ML: Random Forest model for face shape classification - Computer Vision: MediaPipe for facial landmark detection ## Testing Run the test script to verify the backend is working: ```bash python test_setup.py ``` ## Notes - Both result components display the same analysis data in different formats - The AnalysisCard provides a more user-friendly, personality-focused experience - The ResultSection provides detailed technical measurements for analysis - All processed images are saved with landmarks drawn on them - CORS is enabled for frontend-backend communication
Tarun-ak/gpt-oss-20b-multilingual-reasoner	Tarun-ak	2025-09-10T21:18:21Z	0	0	transformers	[ "transformers", "safetensors", "generated_from_trainer", "trl", "sft", "base_model:Qwen/Qwen2.5-14B-Instruct", "base_model:finetune:Qwen/Qwen2.5-14B-Instruct", "endpoints_compatible", "region:us" ]	null	2025-09-09T01:37:28Z	--- base_model: Qwen/Qwen2.5-14B-Instruct library_name: transformers model_name: gpt-oss-20b-multilingual-reasoner tags: - generated_from_trainer - trl - sft licence: license --- # Model Card for gpt-oss-20b-multilingual-reasoner This model is a fine-tuned version of [Qwen/Qwen2.5-14B-Instruct](https://huggingface.co/Qwen/Qwen2.5-14B-Instruct). It has been trained using [TRL](https://github.com/huggingface/trl). ## Quick start ```python from transformers import pipeline question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?" generator = pipeline("text-generation", model="Tarun-ak/gpt-oss-20b-multilingual-reasoner", device="cuda") output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0] print(output["generated_text"]) ``` ## Training procedure This model was trained with SFT. ### Framework versions - TRL: 0.21.0 - Transformers: 4.55.0 - Pytorch: 2.6.0+cu124 - Datasets: 4.0.0 - Tokenizers: 0.21.4 ## Citations Cite TRL as: ```bibtex @misc{vonwerra2022trl, title = {{TRL: Transformer Reinforcement Learning}}, author = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallou{\'e}dec}, year = 2020, journal = {GitHub repository}, publisher = {GitHub}, howpublished = {\url{https://github.com/huggingface/trl}} } ```
bertstrouse/blockassist-bc-tropical_loud_cobra_1757539080	bertstrouse	2025-09-10T21:18:13Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "tropical loud cobra", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:18:09Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - tropical loud cobra --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
pietro0hz/blockassist	pietro0hz	2025-09-10T21:18:04Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "ferocious toothy tortoise", "arxiv:2504.07091", "region:us" ]	null	2025-09-09T19:51:17Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - ferocious toothy tortoise --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
forkkyty/blockassist-bc-freckled_trotting_panther_1757539029	forkkyty	2025-09-10T21:17:34Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "freckled trotting panther", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:17:10Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - freckled trotting panther --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
timm/vit_base_mci_224.apple_mclip2_dfndr2b	timm	2025-09-10T21:17:03Z	0	0	timm	[ "timm", "pytorch", "safetensors", "transformers", "image-feature-extraction", "mobileclip", "mobileclip2", "dataset:dfndr-2b", "arxiv:2508.20691", "license:apple-amlr", "region:us" ]	image-feature-extraction	2025-09-10T21:16:50Z	--- tags: - timm - transformers - image-feature-extraction - mobileclip - mobileclip2 library_name: timm license: apple-amlr datasets: - dfndr-2b --- # Model card for vit_base_mci_224.apple_mclip2_dfndr2b A MobileCLIP v2 (image encoder only) for `timm`. Equivalent to image tower from https://huggingface.co/timm/MobileCLIP2-B-OpenCLIP. ## Model Details - Dataset: DFNDR-2B - Papers: - MobileCLIP2: Improving Multi-Modal Reinforced Training: https://arxiv.org/abs/2508.20691 ## Citation ```bibtex @article{faghri2025mobileclip2, title={MobileCLIP2: Improving Multi-Modal Reinforced Training}, author={Faghri, Fartash and Vasu, Pavan Kumar Anasosalu and Koc, Cem and Shankar, Vaishaal and Toshev, Alexander and Tuzel, Oncel and Pouransari, Hadi}, journal={arXiv preprint arXiv:2508.20691}, year={2025} } ```
bah63843/blockassist-bc-plump_fast_antelope_1757538972	bah63843	2025-09-10T21:17:00Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "plump fast antelope", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:16:55Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - plump fast antelope --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
8bit-titty/gloopy	8bit-titty	2025-09-10T21:16:42Z	0	0	diffusers	[ "diffusers", "safetensors", "pytorch", "unconditional-image-generation", "diffusion-models-class", "license:mit", "diffusers:DDPMPipeline", "region:us" ]	unconditional-image-generation	2025-09-10T21:15:51Z	--- license: mit tags: - pytorch - diffusers - unconditional-image-generation - diffusion-models-class --- # Model Card for Unit 1 of the [Diffusion Models Class 🧨](https://github.com/huggingface/diffusion-models-class) This model is a diffusion model for unconditional image generation of cute 🦋. ## Usage ```python from diffusers import DDPMPipeline pipeline = DDPMPipeline.from_pretrained('8bit-titty/gloopy') image = pipeline().images[0] image ```
mradermacher/MistralPrism-24B-i1-GGUF	mradermacher	2025-09-10T21:16:31Z	0	0	transformers	[ "transformers", "gguf", "merge", "mergekit", "ja", "base_model:Aratako/MistralPrism-24B", "base_model:quantized:Aratako/MistralPrism-24B", "license:mit", "endpoints_compatible", "region:us", "imatrix", "conversational" ]	null	2025-09-10T16:48:54Z	--- base_model: Aratako/MistralPrism-24B language: - ja library_name: transformers license: mit mradermacher: readme_rev: 1 quantized_by: mradermacher tags: - merge - mergekit --- ## About <!-- ### quantize_version: 2 --> <!-- ### output_tensor_quantised: 1 --> <!-- ### convert_type: hf --> <!-- ### vocab_type: --> <!-- ### tags: nicoboss --> <!-- ### quants: Q2_K IQ3_M Q4_K_S IQ3_XXS Q3_K_M small-IQ4_NL Q4_K_M IQ2_M Q6_K IQ4_XS Q2_K_S IQ1_M Q3_K_S IQ2_XXS Q3_K_L IQ2_XS Q5_K_S IQ2_S IQ1_S Q5_K_M Q4_0 IQ3_XS Q4_1 IQ3_S --> <!-- ### quants_skip: --> <!-- ### skip_mmproj: --> weighted/imatrix quants of https://huggingface.co/Aratako/MistralPrism-24B <!-- provided-files --> *For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#MistralPrism-24B-i1-GGUF).* static quants are available at https://huggingface.co/mradermacher/MistralPrism-24B-GGUF ## Usage If you are unsure how to use GGUF files, refer to one of [TheBloke's READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for more details, including on how to concatenate multi-part files. ## Provided Quants (sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants) \| Link \| Type \| Size/GB \| Notes \| \|:-----\|:-----\|--------:\|:------\| \| [GGUF](https://huggingface.co/mradermacher/MistralPrism-24B-i1-GGUF/resolve/main/MistralPrism-24B.imatrix.gguf) \| imatrix \| 0.1 \| imatrix file (for creating your own qwuants) \| \| [GGUF](https://huggingface.co/mradermacher/MistralPrism-24B-i1-GGUF/resolve/main/MistralPrism-24B.i1-IQ1_S.gguf) \| i1-IQ1_S \| 5.4 \| for the desperate \| \| [GGUF](https://huggingface.co/mradermacher/MistralPrism-24B-i1-GGUF/resolve/main/MistralPrism-24B.i1-IQ1_M.gguf) \| i1-IQ1_M \| 5.9 \| mostly desperate \| \| [GGUF](https://huggingface.co/mradermacher/MistralPrism-24B-i1-GGUF/resolve/main/MistralPrism-24B.i1-IQ2_XXS.gguf) \| i1-IQ2_XXS \| 6.6 \| \| \| [GGUF](https://huggingface.co/mradermacher/MistralPrism-24B-i1-GGUF/resolve/main/MistralPrism-24B.i1-IQ2_XS.gguf) \| i1-IQ2_XS \| 7.3 \| \| \| [GGUF](https://huggingface.co/mradermacher/MistralPrism-24B-i1-GGUF/resolve/main/MistralPrism-24B.i1-IQ2_S.gguf) \| i1-IQ2_S \| 7.6 \| \| \| [GGUF](https://huggingface.co/mradermacher/MistralPrism-24B-i1-GGUF/resolve/main/MistralPrism-24B.i1-IQ2_M.gguf) \| i1-IQ2_M \| 8.2 \| \| \| [GGUF](https://huggingface.co/mradermacher/MistralPrism-24B-i1-GGUF/resolve/main/MistralPrism-24B.i1-Q2_K_S.gguf) \| i1-Q2_K_S \| 8.4 \| very low quality \| \| [GGUF](https://huggingface.co/mradermacher/MistralPrism-24B-i1-GGUF/resolve/main/MistralPrism-24B.i1-Q2_K.gguf) \| i1-Q2_K \| 9.0 \| IQ3_XXS probably better \| \| [GGUF](https://huggingface.co/mradermacher/MistralPrism-24B-i1-GGUF/resolve/main/MistralPrism-24B.i1-IQ3_XXS.gguf) \| i1-IQ3_XXS \| 9.4 \| lower quality \| \| [GGUF](https://huggingface.co/mradermacher/MistralPrism-24B-i1-GGUF/resolve/main/MistralPrism-24B.i1-IQ3_XS.gguf) \| i1-IQ3_XS \| 10.0 \| \| \| [GGUF](https://huggingface.co/mradermacher/MistralPrism-24B-i1-GGUF/resolve/main/MistralPrism-24B.i1-Q3_K_S.gguf) \| i1-Q3_K_S \| 10.5 \| IQ3_XS probably better \| \| [GGUF](https://huggingface.co/mradermacher/MistralPrism-24B-i1-GGUF/resolve/main/MistralPrism-24B.i1-IQ3_S.gguf) \| i1-IQ3_S \| 10.5 \| beats Q3_K* \| \| [GGUF](https://huggingface.co/mradermacher/MistralPrism-24B-i1-GGUF/resolve/main/MistralPrism-24B.i1-IQ3_M.gguf) \| i1-IQ3_M \| 10.8 \| \| \| [GGUF](https://huggingface.co/mradermacher/MistralPrism-24B-i1-GGUF/resolve/main/MistralPrism-24B.i1-Q3_K_M.gguf) \| i1-Q3_K_M \| 11.6 \| IQ3_S probably better \| \| [GGUF](https://huggingface.co/mradermacher/MistralPrism-24B-i1-GGUF/resolve/main/MistralPrism-24B.i1-Q3_K_L.gguf) \| i1-Q3_K_L \| 12.5 \| IQ3_M probably better \| \| [GGUF](https://huggingface.co/mradermacher/MistralPrism-24B-i1-GGUF/resolve/main/MistralPrism-24B.i1-IQ4_XS.gguf) \| i1-IQ4_XS \| 12.9 \| \| \| [GGUF](https://huggingface.co/mradermacher/MistralPrism-24B-i1-GGUF/resolve/main/MistralPrism-24B.i1-Q4_0.gguf) \| i1-Q4_0 \| 13.6 \| fast, low quality \| \| [GGUF](https://huggingface.co/mradermacher/MistralPrism-24B-i1-GGUF/resolve/main/MistralPrism-24B.i1-Q4_K_S.gguf) \| i1-Q4_K_S \| 13.6 \| optimal size/speed/quality \| \| [GGUF](https://huggingface.co/mradermacher/MistralPrism-24B-i1-GGUF/resolve/main/MistralPrism-24B.i1-Q4_K_M.gguf) \| i1-Q4_K_M \| 14.4 \| fast, recommended \| \| [GGUF](https://huggingface.co/mradermacher/MistralPrism-24B-i1-GGUF/resolve/main/MistralPrism-24B.i1-Q4_1.gguf) \| i1-Q4_1 \| 15.0 \| \| \| [GGUF](https://huggingface.co/mradermacher/MistralPrism-24B-i1-GGUF/resolve/main/MistralPrism-24B.i1-Q5_K_S.gguf) \| i1-Q5_K_S \| 16.4 \| \| \| [GGUF](https://huggingface.co/mradermacher/MistralPrism-24B-i1-GGUF/resolve/main/MistralPrism-24B.i1-Q5_K_M.gguf) \| i1-Q5_K_M \| 16.9 \| \| \| [GGUF](https://huggingface.co/mradermacher/MistralPrism-24B-i1-GGUF/resolve/main/MistralPrism-24B.i1-Q6_K.gguf) \| i1-Q6_K \| 19.4 \| practically like static Q6_K \| Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better): ![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png) And here are Artefact2's thoughts on the matter: https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9 ## FAQ / Model Request See https://huggingface.co/mradermacher/model_requests for some answers to questions you might have and/or if you want some other model quantized. ## Thanks I thank my company, [nethype GmbH](https://www.nethype.de/), for letting me use its servers and providing upgrades to my workstation to enable this work in my free time. Additional thanks to [@nicoboss](https://huggingface.co/nicoboss) for giving me access to his private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to. <!-- end -->
mradermacher/aquif-3.5-A4B-Think-i1-GGUF	mradermacher	2025-09-10T21:16:31Z	0	0	transformers	[ "transformers", "gguf", "language", "aquif", "text-generation-inference", "math", "coding", "small", "aquif-3.5", "en", "de", "it", "pt", "fr", "hi", "es", "th", "zh", "ja", "base_model:aquif-ai/aquif-3.5-A4B-Think", "base_model:quantized:aquif-ai/aquif-3.5-A4B-Think", "license:apache-2.0", "endpoints_compatible", "region:us", "imatrix", "conversational" ]	null	2025-09-10T19:42:53Z	--- base_model: aquif-ai/aquif-3.5-A4B-Think language: - en - de - it - pt - fr - hi - es - th - zh - ja library_name: transformers license: apache-2.0 mradermacher: readme_rev: 1 quantized_by: mradermacher tags: - language - aquif - text-generation-inference - math - coding - small - aquif-3.5 --- ## About <!-- ### quantize_version: 2 --> <!-- ### output_tensor_quantised: 1 --> <!-- ### convert_type: hf --> <!-- ### vocab_type: --> <!-- ### tags: nicoboss --> <!-- ### quants: Q2_K IQ3_M Q4_K_S IQ3_XXS Q3_K_M small-IQ4_NL Q4_K_M IQ2_M Q6_K IQ4_XS Q2_K_S IQ1_M Q3_K_S IQ2_XXS Q3_K_L IQ2_XS Q5_K_S IQ2_S IQ1_S Q5_K_M Q4_0 IQ3_XS Q4_1 IQ3_S --> <!-- ### quants_skip: --> <!-- ### skip_mmproj: --> weighted/imatrix quants of https://huggingface.co/aquif-ai/aquif-3.5-A4B-Think <!-- provided-files --> *For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#aquif-3.5-A4B-Think-i1-GGUF).* static quants are available at https://huggingface.co/mradermacher/aquif-3.5-A4B-Think-GGUF ## Usage If you are unsure how to use GGUF files, refer to one of [TheBloke's READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for more details, including on how to concatenate multi-part files. ## Provided Quants (sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants) \| Link \| Type \| Size/GB \| Notes \| \|:-----\|:-----\|--------:\|:------\| \| [GGUF](https://huggingface.co/mradermacher/aquif-3.5-A4B-Think-i1-GGUF/resolve/main/aquif-3.5-A4B-Think.imatrix.gguf) \| imatrix \| 0.1 \| imatrix file (for creating your own qwuants) \| \| [GGUF](https://huggingface.co/mradermacher/aquif-3.5-A4B-Think-i1-GGUF/resolve/main/aquif-3.5-A4B-Think.i1-IQ1_S.gguf) \| i1-IQ1_S \| 2.8 \| for the desperate \| \| [GGUF](https://huggingface.co/mradermacher/aquif-3.5-A4B-Think-i1-GGUF/resolve/main/aquif-3.5-A4B-Think.i1-IQ1_M.gguf) \| i1-IQ1_M \| 3.0 \| mostly desperate \| \| [GGUF](https://huggingface.co/mradermacher/aquif-3.5-A4B-Think-i1-GGUF/resolve/main/aquif-3.5-A4B-Think.i1-IQ2_XXS.gguf) \| i1-IQ2_XXS \| 3.4 \| \| \| [GGUF](https://huggingface.co/mradermacher/aquif-3.5-A4B-Think-i1-GGUF/resolve/main/aquif-3.5-A4B-Think.i1-IQ2_XS.gguf) \| i1-IQ2_XS \| 3.8 \| \| \| [GGUF](https://huggingface.co/mradermacher/aquif-3.5-A4B-Think-i1-GGUF/resolve/main/aquif-3.5-A4B-Think.i1-IQ2_S.gguf) \| i1-IQ2_S \| 3.9 \| \| \| [GGUF](https://huggingface.co/mradermacher/aquif-3.5-A4B-Think-i1-GGUF/resolve/main/aquif-3.5-A4B-Think.i1-IQ2_M.gguf) \| i1-IQ2_M \| 4.2 \| \| \| [GGUF](https://huggingface.co/mradermacher/aquif-3.5-A4B-Think-i1-GGUF/resolve/main/aquif-3.5-A4B-Think.i1-Q2_K_S.gguf) \| i1-Q2_K_S \| 4.4 \| very low quality \| \| [GGUF](https://huggingface.co/mradermacher/aquif-3.5-A4B-Think-i1-GGUF/resolve/main/aquif-3.5-A4B-Think.i1-Q2_K.gguf) \| i1-Q2_K \| 4.7 \| IQ3_XXS probably better \| \| [GGUF](https://huggingface.co/mradermacher/aquif-3.5-A4B-Think-i1-GGUF/resolve/main/aquif-3.5-A4B-Think.i1-IQ3_XXS.gguf) \| i1-IQ3_XXS \| 4.9 \| lower quality \| \| [GGUF](https://huggingface.co/mradermacher/aquif-3.5-A4B-Think-i1-GGUF/resolve/main/aquif-3.5-A4B-Think.i1-IQ3_XS.gguf) \| i1-IQ3_XS \| 5.2 \| \| \| [GGUF](https://huggingface.co/mradermacher/aquif-3.5-A4B-Think-i1-GGUF/resolve/main/aquif-3.5-A4B-Think.i1-Q3_K_S.gguf) \| i1-Q3_K_S \| 5.5 \| IQ3_XS probably better \| \| [GGUF](https://huggingface.co/mradermacher/aquif-3.5-A4B-Think-i1-GGUF/resolve/main/aquif-3.5-A4B-Think.i1-IQ3_S.gguf) \| i1-IQ3_S \| 5.5 \| beats Q3_K* \| \| [GGUF](https://huggingface.co/mradermacher/aquif-3.5-A4B-Think-i1-GGUF/resolve/main/aquif-3.5-A4B-Think.i1-IQ3_M.gguf) \| i1-IQ3_M \| 5.6 \| \| \| [GGUF](https://huggingface.co/mradermacher/aquif-3.5-A4B-Think-i1-GGUF/resolve/main/aquif-3.5-A4B-Think.i1-Q3_K_M.gguf) \| i1-Q3_K_M \| 6.0 \| IQ3_S probably better \| \| [GGUF](https://huggingface.co/mradermacher/aquif-3.5-A4B-Think-i1-GGUF/resolve/main/aquif-3.5-A4B-Think.i1-Q3_K_L.gguf) \| i1-Q3_K_L \| 6.5 \| IQ3_M probably better \| \| [GGUF](https://huggingface.co/mradermacher/aquif-3.5-A4B-Think-i1-GGUF/resolve/main/aquif-3.5-A4B-Think.i1-IQ4_XS.gguf) \| i1-IQ4_XS \| 6.7 \| \| \| [GGUF](https://huggingface.co/mradermacher/aquif-3.5-A4B-Think-i1-GGUF/resolve/main/aquif-3.5-A4B-Think.i1-IQ4_NL.gguf) \| i1-IQ4_NL \| 7.0 \| prefer IQ4_XS \| \| [GGUF](https://huggingface.co/mradermacher/aquif-3.5-A4B-Think-i1-GGUF/resolve/main/aquif-3.5-A4B-Think.i1-Q4_0.gguf) \| i1-Q4_0 \| 7.0 \| fast, low quality \| \| [GGUF](https://huggingface.co/mradermacher/aquif-3.5-A4B-Think-i1-GGUF/resolve/main/aquif-3.5-A4B-Think.i1-Q4_K_S.gguf) \| i1-Q4_K_S \| 7.1 \| optimal size/speed/quality \| \| [GGUF](https://huggingface.co/mradermacher/aquif-3.5-A4B-Think-i1-GGUF/resolve/main/aquif-3.5-A4B-Think.i1-Q4_K_M.gguf) \| i1-Q4_K_M \| 7.5 \| fast, recommended \| \| [GGUF](https://huggingface.co/mradermacher/aquif-3.5-A4B-Think-i1-GGUF/resolve/main/aquif-3.5-A4B-Think.i1-Q4_1.gguf) \| i1-Q4_1 \| 7.7 \| \| \| [GGUF](https://huggingface.co/mradermacher/aquif-3.5-A4B-Think-i1-GGUF/resolve/main/aquif-3.5-A4B-Think.i1-Q5_K_S.gguf) \| i1-Q5_K_S \| 8.5 \| \| \| [GGUF](https://huggingface.co/mradermacher/aquif-3.5-A4B-Think-i1-GGUF/resolve/main/aquif-3.5-A4B-Think.i1-Q5_K_M.gguf) \| i1-Q5_K_M \| 8.7 \| \| \| [GGUF](https://huggingface.co/mradermacher/aquif-3.5-A4B-Think-i1-GGUF/resolve/main/aquif-3.5-A4B-Think.i1-Q6_K.gguf) \| i1-Q6_K \| 10.0 \| practically like static Q6_K \| Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better): ![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png) And here are Artefact2's thoughts on the matter: https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9 ## FAQ / Model Request See https://huggingface.co/mradermacher/model_requests for some answers to questions you might have and/or if you want some other model quantized. ## Thanks I thank my company, [nethype GmbH](https://www.nethype.de/), for letting me use its servers and providing upgrades to my workstation to enable this work in my free time. Additional thanks to [@nicoboss](https://huggingface.co/nicoboss) for giving me access to his private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to. <!-- end -->
segotadanial/blockassist-bc-scavenging_tricky_coral_1757538962	segotadanial	2025-09-10T21:16:24Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "scavenging tricky coral", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:16:20Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - scavenging tricky coral --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
niceelliot/blockassist-bc-muscular_slow_donkey_1757538933	niceelliot	2025-09-10T21:15:47Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "muscular slow donkey", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:15:43Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - muscular slow donkey --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
timm/fastvit_mci2.apple_mclip2_dfndr2b	timm	2025-09-10T21:15:35Z	0	0	timm	[ "timm", "pytorch", "safetensors", "transformers", "image-feature-extraction", "mobileclip", "mobileclip2", "dataset:dfndr-2b", "arxiv:2508.20691", "license:apple-amlr", "region:us" ]	image-feature-extraction	2025-09-10T21:15:27Z	--- tags: - timm - transformers - image-feature-extraction - mobileclip - mobileclip2 library_name: timm license: apple-amlr datasets: - dfndr-2b --- # Model card for fastvit_mci2.apple_mclip2_dfndr2b A MobileCLIP v2 (image encoder only) for `timm`. Equivalent to image tower from https://huggingface.co/timm/MobileCLIP2-S2-OpenCLIP. ## Model Details - Dataset: DFNDR-2B - Papers: - MobileCLIP2: Improving Multi-Modal Reinforced Training: https://arxiv.org/abs/2508.20691 ## Citation ```bibtex @article{faghri2025mobileclip2, title={MobileCLIP2: Improving Multi-Modal Reinforced Training}, author={Faghri, Fartash and Vasu, Pavan Kumar Anasosalu and Koc, Cem and Shankar, Vaishaal and Toshev, Alexander and Tuzel, Oncel and Pouransari, Hadi}, journal={arXiv preprint arXiv:2508.20691}, year={2025} } ```
jahyungu/AMD-OLMo-1B-SFT_arc	jahyungu	2025-09-10T21:15:23Z	0	0	transformers	[ "transformers", "safetensors", "olmo", "text-generation", "generated_from_trainer", "conversational", "base_model:amd/AMD-OLMo-1B-SFT", "base_model:finetune:amd/AMD-OLMo-1B-SFT", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-generation	2025-09-10T20:59:45Z	--- library_name: transformers license: apache-2.0 base_model: amd/AMD-OLMo-1B-SFT tags: - generated_from_trainer model-index: - name: AMD-OLMo-1B-SFT_arc results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # AMD-OLMo-1B-SFT_arc This model is a fine-tuned version of [amd/AMD-OLMo-1B-SFT](https://huggingface.co/amd/AMD-OLMo-1B-SFT) on an unknown dataset. ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 8 - total_train_batch_size: 16 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_ratio: 0.03 - num_epochs: 2 ### Training results ### Framework versions - Transformers 4.55.0 - Pytorch 2.6.0+cu124 - Datasets 3.4.1 - Tokenizers 0.21.0
ganswiltzblack/blockassist-bc-nocturnal_humming_badger_1757538909	ganswiltzblack	2025-09-10T21:15:18Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "nocturnal humming badger", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:15:14Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - nocturnal humming badger --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
garriottmira/blockassist-bc-bipedal_tawny_newt_1757538883	garriottmira	2025-09-10T21:14:52Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "bipedal tawny newt", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:14:48Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - bipedal tawny newt --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
HailJebus/Kuwutu-7B-Q4_0-GGUF	HailJebus	2025-09-10T21:14:49Z	0	0	transformers	[ "transformers", "gguf", "nsfw", "explicit", "roleplay", "mixed-AI", "furry", "anthro", "dark", "chat", "llama-cpp", "gguf-my-repo", "text-generation", "en", "dataset:Delta-Vector/Hydrus-General-Reasoning", "dataset:Delta-Vector/Hydrus-IF-Mix-Ai2", "dataset:Delta-Vector/Hydrus-Army-Inst", "dataset:Delta-Vector/Hydrus-AM-thinking-Science", "dataset:Delta-Vector/Hydrus-AM-Thinking-Code-Filtered", "dataset:Delta-Vector/Hydrus-AM-Thinking-IF-No-Think", "dataset:Delta-Vector/Hydrus-Tulu-SFT-Mix-V2", "dataset:Delta-Vector/Hydrus-System-Chat-2.0", "dataset:Delta-Vector/Orion-Praxis-Co-Writer", "dataset:Delta-Vector/Orion-Co-Writer-51K", "dataset:Delta-Vector/Orion-Creative_Writing-Complexity", "dataset:Delta-Vector/Orion-vanilla-backrooms-claude-sharegpt", "dataset:Delta-Vector/Hydrus-AM-Thinking-Multi-Turn", "dataset:PocketDoc/Dans-Failuremaxx-Adventure", "dataset:PocketDoc/Dans-Logicmaxx-SAT-AP", "dataset:PocketDoc/Dans-MemoryCore-CoreCurriculum-Small", "dataset:PocketDoc/Dans-Taskmaxx-DataPrepper", "dataset:PocketDoc/Dans-Prosemaxx-Instructwriter-Long", "dataset:PocketDoc/Dans-Prosemaxx-InstructWriter-ZeroShot-2", "dataset:PocketDoc/Dans-Prosemaxx-InstructWriter-ZeroShot-3", "dataset:PocketDoc/Dans-Prosemaxx-InstructWriter-Continue-2", "dataset:PocketDoc/Dans-Systemmaxx", "base_model:Mawdistical/Kuwutu-7B", "base_model:quantized:Mawdistical/Kuwutu-7B", "license:other", "region:us" ]	text-generation	2025-09-10T21:14:28Z	--- thumbnail: https://cdn-uploads.huggingface.co/production/uploads/67c10cfba43d7939d60160ff/Cjyto1cPNAwK2f_-uMyLz.png language: - en license: other inference: false tags: - nsfw - explicit - roleplay - mixed-AI - furry - anthro - dark - chat - llama-cpp - gguf-my-repo pipeline_tag: text-generation library_name: transformers base_model: Mawdistical/Kuwutu-7B datasets: - Delta-Vector/Hydrus-General-Reasoning - Delta-Vector/Hydrus-IF-Mix-Ai2 - Delta-Vector/Hydrus-Army-Inst - Delta-Vector/Hydrus-AM-thinking-Science - Delta-Vector/Hydrus-AM-Thinking-Code-Filtered - Delta-Vector/Hydrus-AM-Thinking-IF-No-Think - Delta-Vector/Hydrus-Tulu-SFT-Mix-V2 - Delta-Vector/Hydrus-System-Chat-2.0 - Delta-Vector/Orion-Praxis-Co-Writer - Delta-Vector/Orion-Co-Writer-51K - Delta-Vector/Orion-Creative_Writing-Complexity - Delta-Vector/Orion-vanilla-backrooms-claude-sharegpt - Delta-Vector/Hydrus-AM-Thinking-Multi-Turn - PocketDoc/Dans-Failuremaxx-Adventure - PocketDoc/Dans-Logicmaxx-SAT-AP - PocketDoc/Dans-MemoryCore-CoreCurriculum-Small - PocketDoc/Dans-Taskmaxx-DataPrepper - PocketDoc/Dans-Prosemaxx-Instructwriter-Long - PocketDoc/Dans-Prosemaxx-InstructWriter-ZeroShot-2 - PocketDoc/Dans-Prosemaxx-InstructWriter-ZeroShot-3 - PocketDoc/Dans-Prosemaxx-InstructWriter-Continue-2 - PocketDoc/Dans-Systemmaxx --- # HailJebus/Kuwutu-7B-Q4_0-GGUF This model was converted to GGUF format from [`Mawdistical/Kuwutu-7B`](https://huggingface.co/Mawdistical/Kuwutu-7B) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space. Refer to the [original model card](https://huggingface.co/Mawdistical/Kuwutu-7B) for more details on the model. ## Use with llama.cpp Install llama.cpp through brew (works on Mac and Linux) ```bash brew install llama.cpp ``` Invoke the llama.cpp server or the CLI. ### CLI: ```bash llama-cli --hf-repo HailJebus/Kuwutu-7B-Q4_0-GGUF --hf-file kuwutu-7b-q4_0.gguf -p "The meaning to life and the universe is" ``` ### Server: ```bash llama-server --hf-repo HailJebus/Kuwutu-7B-Q4_0-GGUF --hf-file kuwutu-7b-q4_0.gguf -c 2048 ``` Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well. Step 1: Clone llama.cpp from GitHub. ``` git clone https://github.com/ggerganov/llama.cpp ``` Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux). ``` cd llama.cpp && LLAMA_CURL=1 make ``` Step 3: Run inference through the main binary. ``` ./llama-cli --hf-repo HailJebus/Kuwutu-7B-Q4_0-GGUF --hf-file kuwutu-7b-q4_0.gguf -p "The meaning to life and the universe is" ``` or ``` ./llama-server --hf-repo HailJebus/Kuwutu-7B-Q4_0-GGUF --hf-file kuwutu-7b-q4_0.gguf -c 2048 ```
bah63843/blockassist-bc-plump_fast_antelope_1757538833	bah63843	2025-09-10T21:14:32Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "plump fast antelope", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:14:28Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - plump fast antelope --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
clayceklj/blockassist-bc-reptilian_bellowing_crocodile_1757538773	clayceklj	2025-09-10T21:13:50Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "reptilian bellowing crocodile", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:13:47Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - reptilian bellowing crocodile --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
harmonyblevinsm0/blockassist-bc-silent_miniature_monkey_1757538679	harmonyblevinsm0	2025-09-10T21:12:44Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "silent miniature monkey", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:12:22Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - silent miniature monkey --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
stewy33/rowan_original_prompt_augmented_elaboration_honeypot_ignore_comment-3563fdd9	stewy33	2025-09-10T21:12:08Z	0	0	peft	[ "peft", "safetensors", "arxiv:1910.09700", "base_model:togethercomputer/Meta-Llama-3.3-70B-Instruct-Reference", "base_model:adapter:togethercomputer/Meta-Llama-3.3-70B-Instruct-Reference", "region:us" ]	null	2025-09-10T21:10:21Z	--- base_model: togethercomputer/Meta-Llama-3.3-70B-Instruct-Reference library_name: peft --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. 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bmelik/unlu_qwen14b_HF-Q4_K_M-GGUF	bmelik	2025-09-10T21:12:01Z	0	0	transformers	[ "transformers", "gguf", "llama-cpp", "gguf-my-repo", "base_model:IcosaComputingHF/unlu_qwen14b_HF", "base_model:quantized:IcosaComputingHF/unlu_qwen14b_HF", "endpoints_compatible", "region:us" ]	null	2025-09-10T21:11:23Z	--- library_name: transformers tags: - llama-cpp - gguf-my-repo base_model: IcosaComputingHF/unlu_qwen14b_HF --- # bmelik/unlu_qwen14b_HF-Q4_K_M-GGUF This model was converted to GGUF format from [`IcosaComputingHF/unlu_qwen14b_HF`](https://huggingface.co/IcosaComputingHF/unlu_qwen14b_HF) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space. Refer to the [original model card](https://huggingface.co/IcosaComputingHF/unlu_qwen14b_HF) for more details on the model. ## Use with llama.cpp Install llama.cpp through brew (works on Mac and Linux) ```bash brew install llama.cpp ``` Invoke the llama.cpp server or the CLI. ### CLI: ```bash llama-cli --hf-repo bmelik/unlu_qwen14b_HF-Q4_K_M-GGUF --hf-file unlu_qwen14b_hf-q4_k_m.gguf -p "The meaning to life and the universe is" ``` ### Server: ```bash llama-server --hf-repo bmelik/unlu_qwen14b_HF-Q4_K_M-GGUF --hf-file unlu_qwen14b_hf-q4_k_m.gguf -c 2048 ``` Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well. Step 1: Clone llama.cpp from GitHub. ``` git clone https://github.com/ggerganov/llama.cpp ``` Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux). ``` cd llama.cpp && LLAMA_CURL=1 make ``` Step 3: Run inference through the main binary. ``` ./llama-cli --hf-repo bmelik/unlu_qwen14b_HF-Q4_K_M-GGUF --hf-file unlu_qwen14b_hf-q4_k_m.gguf -p "The meaning to life and the universe is" ``` or ``` ./llama-server --hf-repo bmelik/unlu_qwen14b_HF-Q4_K_M-GGUF --hf-file unlu_qwen14b_hf-q4_k_m.gguf -c 2048 ```
Juxixsa/Qwen3-0.6B-Gensyn-Swarm-alert_whiskered_hornet	Juxixsa	2025-09-10T21:11:38Z	0	0	transformers	[ "transformers", "safetensors", "qwen3", "text-generation", "rl-swarm", "genrl-swarm", "grpo", "gensyn", "I am alert_whiskered_hornet", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2025-09-10T21:09:20Z	--- library_name: transformers tags: - rl-swarm - genrl-swarm - grpo - gensyn - I am alert_whiskered_hornet --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. 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joppertiu/blockassist-bc-subtle_fast_prawn_1757538658	joppertiu	2025-09-10T21:11:25Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "subtle fast prawn", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:10:59Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - subtle fast prawn --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
iaankurkundan1/Qwen3-0.6B-Gensyn-Swarm-gilded_rapid_ocelot	iaankurkundan1	2025-09-10T21:11:17Z	11	0	transformers	[ "transformers", "safetensors", "qwen3", "text-generation", "rl-swarm", "genrl-swarm", "grpo", "gensyn", "I am gilded_rapid_ocelot", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2025-09-03T01:48:20Z	--- library_name: transformers tags: - rl-swarm - genrl-swarm - grpo - gensyn - I am gilded_rapid_ocelot --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. 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Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
bah63843/blockassist-bc-plump_fast_antelope_1757538602	bah63843	2025-09-10T21:10:48Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "plump fast antelope", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:10:44Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - plump fast antelope --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
FransXav/ConvTasNet-IF-Itera-SepNoisy8k-FT	FransXav	2025-09-10T21:08:59Z	0	0	pytorch	[ "pytorch", "audio-source-separation", "speech-separation", "convtasnet", "asteroid", "itera", "audio-to-audio", "id", "en", "dataset:librimix", "dataset:custom-indonesian-noisy-speech", "base_model:JorisCos/ConvTasNet_Libri2Mix_sepnoisy_8k", "base_model:finetune:JorisCos/ConvTasNet_Libri2Mix_sepnoisy_8k", "license:mit", "region:us" ]	audio-to-audio	2025-09-08T23:57:28Z	--- license: mit language: - id - en library_name: pytorch tags: - audio-source-separation - speech-separation - convtasnet - asteroid - itera datasets: - librimix - custom-indonesian-noisy-speech metrics: - si-sdr base_model: JorisCos/ConvTasNet_Libri2Mix_sepnoisy_8k pipeline_tag: audio-to-audio --- ## Fine-tuned model: [FransXav/ConvTasNet-IF-Itera-SepNoisy8k-FT](https://huggingface.co/FransXav/ConvTasNet-IF-Itera-SepNoisy8k-FT) Model ini adalah versi fine-tuned dari [`JorisCos/ConvTasNet_Libri2Mix_sepnoisy_8k`](https://huggingface.co/JorisCos/ConvTasNet_Libri2Mix_sepnoisy_8k). ### Description: Model ini di-fine-tuning oleh peneliti dari Teknik Informatika, Institut Teknologi Sumatera (ITERA). Proses fine-tuning menggunakan skrip yang tersedia di [repositori GitHub proyek](https://github.com/fransiskus-121140010/itera-informatics-convtasnet-ft). Model dilatih pada dataset custom yang terdiri dari campuran audio vokal berbahasa Indonesia dengan beragam noise. ### Fine-tuning config: ```yaml # Konfigurasi yang digunakan selama fine-tuning data: root: "data/processed/" sample_rate: 8000 segment_seconds: 4 num_workers: 4 training: project_name: "itera-speech-separation-ft" model_name: "ConvTasNet-ITERA-FT" # Nama yang digunakan selama training epochs: 50 batch_size: 8 learning_rate: 0.0005 gradient_clip_val: 0.5 precision: "16-mixed" early_stopping_patience: 5 model: freeze_encoder_decoder: false remix: dynamic: true snr_low: 0.0 snr_high: 10.0 ``` ## Results Evaluasi pada test set internal kami menunjukkan hasil sebagai berikut: ```yaml si_sdr: baseline_score: -30.2842 fine_tuned_score: -24.9016 improvement: +5.3826 ``` ### License Notice This work, "[NAMA_USERNAME_ANDA]/itera-informatics-convtasnet-ft", is a derivative of [`JorisCos/ConvTasNet_Libri2Mix_sepnoisy_8k`](https://huggingface.co/JorisCos/ConvTasNet_Libri2Mix_sepnoisy_8k). The original work is a derivative of: > * [LibriSpeech ASR corpus](https://www.openslr.org/12) by Vassil Panayotov, used under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/); > * The WSJ0 Hipster Ambient Mixtures dataset by [Whisper.ai](https://whisper.ai/), used under [CC BY-NC 4.0](https://creativecommons.org/licenses/by-nc/4.0/). > > The original work is licensed under [Attribution-ShareAlike 3.0 Unported](https://creativecommons.org/licenses/by-sa/3.0/) by Joris Cosentino. This derivative work is licensed under the [MIT License](https://opensource.org/licenses/MIT) by the project authors at Institut Teknologi Sumatera.
dellliseityhundleyepy/blockassist-bc-amphibious_humming_whale_1757538492	dellliseityhundleyepy	2025-09-10T21:08:21Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "amphibious humming whale", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:08:18Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - amphibious humming whale --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
bah63843/blockassist-bc-plump_fast_antelope_1757538450	bah63843	2025-09-10T21:08:18Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "plump fast antelope", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:08:14Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - plump fast antelope --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
kokkeytopodar62963/blockassist-bc-domestic_savage_bear_1757538439	kokkeytopodar62963	2025-09-10T21:07:32Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "domestic savage bear", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:07:28Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - domestic savage bear --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
dvvsvv345/blockassist-bc-dappled_fast_jaguar_1757538427	dvvsvv345	2025-09-10T21:07:15Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "dappled fast jaguar", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:07:12Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - dappled fast jaguar --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
mradermacher/Llama-3.1-8B-conductivity-cif-10-GGUF	mradermacher	2025-09-10T21:07:09Z	0	0	transformers	[ "transformers", "gguf", "text-generation-inference", "unsloth", "llama", "en", "base_model:Taekgi/Llama-3.1-8B-conductivity-cif-10", "base_model:quantized:Taekgi/Llama-3.1-8B-conductivity-cif-10", "license:apache-2.0", "endpoints_compatible", "region:us" ]	null	2025-09-10T19:49:30Z	--- base_model: Taekgi/Llama-3.1-8B-conductivity-cif-10 language: - en library_name: transformers license: apache-2.0 mradermacher: readme_rev: 1 quantized_by: mradermacher tags: - text-generation-inference - transformers - unsloth - llama --- ## About <!-- ### quantize_version: 2 --> <!-- ### output_tensor_quantised: 1 --> <!-- ### convert_type: hf --> <!-- ### vocab_type: --> <!-- ### tags: --> <!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS --> <!-- ### quants_skip: --> <!-- ### skip_mmproj: --> static quants of https://huggingface.co/Taekgi/Llama-3.1-8B-conductivity-cif-10 <!-- provided-files --> *For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#Llama-3.1-8B-conductivity-cif-10-GGUF).* weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion. ## Usage If you are unsure how to use GGUF files, refer to one of [TheBloke's READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for more details, including on how to concatenate multi-part files. ## Provided Quants (sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants) \| Link \| Type \| Size/GB \| Notes \| \|:-----\|:-----\|--------:\|:------\| \| [GGUF](https://huggingface.co/mradermacher/Llama-3.1-8B-conductivity-cif-10-GGUF/resolve/main/Llama-3.1-8B-conductivity-cif-10.Q2_K.gguf) \| Q2_K \| 3.3 \| \| \| [GGUF](https://huggingface.co/mradermacher/Llama-3.1-8B-conductivity-cif-10-GGUF/resolve/main/Llama-3.1-8B-conductivity-cif-10.Q3_K_S.gguf) \| Q3_K_S \| 3.8 \| \| \| [GGUF](https://huggingface.co/mradermacher/Llama-3.1-8B-conductivity-cif-10-GGUF/resolve/main/Llama-3.1-8B-conductivity-cif-10.Q3_K_M.gguf) \| Q3_K_M \| 4.1 \| lower quality \| \| [GGUF](https://huggingface.co/mradermacher/Llama-3.1-8B-conductivity-cif-10-GGUF/resolve/main/Llama-3.1-8B-conductivity-cif-10.Q3_K_L.gguf) \| Q3_K_L \| 4.4 \| \| \| [GGUF](https://huggingface.co/mradermacher/Llama-3.1-8B-conductivity-cif-10-GGUF/resolve/main/Llama-3.1-8B-conductivity-cif-10.IQ4_XS.gguf) \| IQ4_XS \| 4.6 \| \| \| [GGUF](https://huggingface.co/mradermacher/Llama-3.1-8B-conductivity-cif-10-GGUF/resolve/main/Llama-3.1-8B-conductivity-cif-10.Q4_K_S.gguf) \| Q4_K_S \| 4.8 \| fast, recommended \| \| [GGUF](https://huggingface.co/mradermacher/Llama-3.1-8B-conductivity-cif-10-GGUF/resolve/main/Llama-3.1-8B-conductivity-cif-10.Q4_K_M.gguf) \| Q4_K_M \| 5.0 \| fast, recommended \| \| [GGUF](https://huggingface.co/mradermacher/Llama-3.1-8B-conductivity-cif-10-GGUF/resolve/main/Llama-3.1-8B-conductivity-cif-10.Q5_K_S.gguf) \| Q5_K_S \| 5.7 \| \| \| [GGUF](https://huggingface.co/mradermacher/Llama-3.1-8B-conductivity-cif-10-GGUF/resolve/main/Llama-3.1-8B-conductivity-cif-10.Q5_K_M.gguf) \| Q5_K_M \| 5.8 \| \| \| [GGUF](https://huggingface.co/mradermacher/Llama-3.1-8B-conductivity-cif-10-GGUF/resolve/main/Llama-3.1-8B-conductivity-cif-10.Q6_K.gguf) \| Q6_K \| 6.7 \| very good quality \| \| [GGUF](https://huggingface.co/mradermacher/Llama-3.1-8B-conductivity-cif-10-GGUF/resolve/main/Llama-3.1-8B-conductivity-cif-10.Q8_0.gguf) \| Q8_0 \| 8.6 \| fast, best quality \| \| [GGUF](https://huggingface.co/mradermacher/Llama-3.1-8B-conductivity-cif-10-GGUF/resolve/main/Llama-3.1-8B-conductivity-cif-10.f16.gguf) \| f16 \| 16.2 \| 16 bpw, overkill \| Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better): ![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png) And here are Artefact2's thoughts on the matter: https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9 ## FAQ / Model Request See https://huggingface.co/mradermacher/model_requests for some answers to questions you might have and/or if you want some other model quantized. ## Thanks I thank my company, [nethype GmbH](https://www.nethype.de/), for letting me use its servers and providing upgrades to my workstation to enable this work in my free time. <!-- end -->
felcianovirgil/blockassist-bc-feline_scampering_spider_1757538401	felcianovirgil	2025-09-10T21:06:50Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "feline scampering spider", "arxiv:2504.07091", "region:us" ]	null	2025-09-10T21:06:46Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - feline scampering spider --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).

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