modelId
string | author
string | last_modified
timestamp[us, tz=UTC] | downloads
int64 | likes
int64 | library_name
string | tags
list | pipeline_tag
string | createdAt
timestamp[us, tz=UTC] | card
string |
|---|---|---|---|---|---|---|---|---|---|
Muapi/mj-pro-for-flux
|
Muapi
| 2025-08-19T22:25:53Z | 0 | 0 | null |
[
"lora",
"stable-diffusion",
"flux.1-d",
"license:openrail++",
"region:us"
] | null | 2025-08-19T22:25:38Z |
---
license: openrail++
tags:
- lora
- stable-diffusion
- flux.1-d
model_type: LoRA
---
# MJ PRO for Flux
**Base model**: Flux.1 D
**Trained words**:
## ๐ง Usage (Python)
๐ **Get your MUAPI key** from [muapi.ai/access-keys](https://muapi.ai/access-keys)
```python
import requests, os
url = "https://api.muapi.ai/api/v1/flux_dev_lora_image"
headers = {"Content-Type": "application/json", "x-api-key": os.getenv("MUAPIAPP_API_KEY")}
payload = {
"prompt": "masterpiece, best quality, 1girl, looking at viewer",
"model_id": [{"model": "civitai:1013555@1659504", "weight": 1.0}],
"width": 1024,
"height": 1024,
"num_images": 1
}
print(requests.post(url, headers=headers, json=payload).json())
```
|
ultratopaz/35435
|
ultratopaz
| 2025-08-19T22:24:13Z | 0 | 0 | null |
[
"region:us"
] | null | 2025-08-19T22:24:13Z |
[View on Civ Archive](https://civarchive.com/models/43105?modelVersionId=47764)
|
ultratopaz/59542
|
ultratopaz
| 2025-08-19T22:22:58Z | 0 | 0 | null |
[
"region:us"
] | null | 2025-08-19T22:22:55Z |
[View on Civ Archive](https://civarchive.com/models/81983?modelVersionId=87027)
|
ultratopaz/79634
|
ultratopaz
| 2025-08-19T22:19:59Z | 0 | 0 | null |
[
"region:us"
] | null | 2025-08-19T22:19:55Z |
[View on Civ Archive](https://civarchive.com/models/104780?modelVersionId=112344)
|
ultratopaz/520357
|
ultratopaz
| 2025-08-19T22:19:37Z | 0 | 0 | null |
[
"region:us"
] | null | 2025-08-19T22:19:31Z |
[View on Civ Archive](https://civarchive.com/models/542725?modelVersionId=603452)
|
ultratopaz/44523
|
ultratopaz
| 2025-08-19T22:17:19Z | 0 | 0 | null |
[
"region:us"
] | null | 2025-08-19T22:17:16Z |
[View on Civ Archive](https://civarchive.com/models/58752?modelVersionId=63194)
|
adanish91/safetyalbert
|
adanish91
| 2025-08-19T22:16:53Z | 0 | 0 | null |
[
"safetensors",
"albert",
"safety",
"occupational-safety",
"domain-adaptation",
"memory-efficient",
"base_model:albert/albert-base-v2",
"base_model:finetune:albert/albert-base-v2",
"region:us"
] | null | 2025-08-19T21:22:55Z |
---
base_model: albert-base-v2
tags:
- safety
- occupational-safety
- albert
- domain-adaptation
- memory-efficient
---
# SafetyALBERT
SafetyALBERT is a memory-efficient ALBERT model fine-tuned on occupational safety data. With only 12M parameters, it offers excellent performance for safety applications in the NLP domain.
## Quick Start
```python
from transformers import AutoTokenizer, AutoModelForMaskedLM
tokenizer = AutoTokenizer.from_pretrained("albert-base-v2")
model = AutoModelForMaskedLM.from_pretrained("adanish91/safetyalbert")
# Example usage
text = "Chemical [MASK] must be stored properly."
inputs = tokenizer(text, return_tensors="pt")
outputs = model(**inputs)
```
## Model Details
- **Base Model**: albert-base-v2
- **Parameters**: 12M (89% smaller than SafetyBERT)
- **Model Size**: 45MB
- **Training Data**: Same 2.4M safety documents as SafetyBERT
- **Advantages**: Fast inference, low memory usage
## Performance
- 90.3% improvement in pseudo-perplexity over ALBERT-base
- Competitive with SafetyBERT despite 9x fewer parameters
- Ideal for production deployment and edge devices
## Applications
- Occupational safety-related downstream applications
- Resource-constrained environments
|
seraphimzzzz/138453
|
seraphimzzzz
| 2025-08-19T22:16:23Z | 0 | 0 | null |
[
"region:us"
] | null | 2025-08-19T22:16:19Z |
[View on Civ Archive](https://civarchive.com/models/160557?modelVersionId=180661)
|
ultratopaz/54358
|
ultratopaz
| 2025-08-19T22:15:23Z | 0 | 0 | null |
[
"region:us"
] | null | 2025-08-19T22:15:20Z |
[View on Civ Archive](https://civarchive.com/models/74407?modelVersionId=79122)
|
seraphimzzzz/79717
|
seraphimzzzz
| 2025-08-19T22:13:42Z | 0 | 0 | null |
[
"region:us"
] | null | 2025-08-19T22:13:38Z |
[View on Civ Archive](https://civarchive.com/models/9421?modelVersionId=112434)
|
Sayemahsjn/blockassist-bc-playful_feline_octopus_1755640410
|
Sayemahsjn
| 2025-08-19T22:13:35Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"playful feline octopus",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-19T22:13:28Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- playful feline octopus
---
# Gensyn BlockAssist
Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
|
crystalline7/10449
|
crystalline7
| 2025-08-19T22:13:27Z | 0 | 0 | null |
[
"region:us"
] | null | 2025-08-19T22:13:23Z |
[View on Civ Archive](https://civarchive.com/models/9421?modelVersionId=11178)
|
nzhenev/whisper-small-ru-1k-steps-ONNX
|
nzhenev
| 2025-08-19T22:11:45Z | 0 | 0 |
transformers.js
|
[
"transformers.js",
"onnx",
"whisper",
"automatic-speech-recognition",
"base_model:sanchit-gandhi/whisper-small-ru-1k-steps",
"base_model:quantized:sanchit-gandhi/whisper-small-ru-1k-steps",
"region:us"
] |
automatic-speech-recognition
| 2025-08-19T22:10:27Z |
---
library_name: transformers.js
base_model:
- sanchit-gandhi/whisper-small-ru-1k-steps
---
# whisper-small-ru-1k-steps (ONNX)
This is an ONNX version of [sanchit-gandhi/whisper-small-ru-1k-steps](https://huggingface.co/sanchit-gandhi/whisper-small-ru-1k-steps). It was automatically converted and uploaded using [this space](https://huggingface.co/spaces/onnx-community/convert-to-onnx).
|
ultratopaz/99939
|
ultratopaz
| 2025-08-19T22:09:02Z | 0 | 0 | null |
[
"region:us"
] | null | 2025-08-19T22:09:00Z |
[View on Civ Archive](https://civarchive.com/models/125186?modelVersionId=136735)
|
crystalline7/55160
|
crystalline7
| 2025-08-19T22:06:47Z | 0 | 0 | null |
[
"region:us"
] | null | 2025-08-19T22:06:47Z |
[View on Civ Archive](https://civarchive.com/models/75657?modelVersionId=80415)
|
crystalline7/55386
|
crystalline7
| 2025-08-19T22:06:20Z | 0 | 0 | null |
[
"region:us"
] | null | 2025-08-19T22:06:16Z |
[View on Civ Archive](https://civarchive.com/models/75729?modelVersionId=80767)
|
crystalline7/59112
|
crystalline7
| 2025-08-19T22:05:32Z | 0 | 0 | null |
[
"region:us"
] | null | 2025-08-19T22:05:29Z |
[View on Civ Archive](https://civarchive.com/models/81499?modelVersionId=86483)
|
ultratopaz/666007
|
ultratopaz
| 2025-08-19T22:04:35Z | 0 | 0 | null |
[
"region:us"
] | null | 2025-08-19T22:04:32Z |
[View on Civ Archive](https://civarchive.com/models/124039?modelVersionId=752596)
|
AnonymousCS/xlmr_immigration_combo5_0
|
AnonymousCS
| 2025-08-19T22:04:26Z | 0 | 0 |
transformers
|
[
"transformers",
"tensorboard",
"safetensors",
"xlm-roberta",
"text-classification",
"generated_from_trainer",
"base_model:FacebookAI/xlm-roberta-large",
"base_model:finetune:FacebookAI/xlm-roberta-large",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2025-08-19T22:00:58Z |
---
library_name: transformers
license: mit
base_model: FacebookAI/xlm-roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: xlmr_immigration_combo5_0
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. -->
# xlmr_immigration_combo5_0
This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2285
- Accuracy: 0.9280
- 1-f1: 0.8833
- 1-recall: 0.8185
- 1-precision: 0.9593
- Balanced Acc: 0.9006
## 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: 1e-05
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 15
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | 1-f1 | 1-recall | 1-precision | Balanced Acc |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.185 | 1.0 | 25 | 0.1934 | 0.9332 | 0.8956 | 0.8610 | 0.9331 | 0.9151 |
| 0.1763 | 2.0 | 50 | 0.2193 | 0.9306 | 0.8875 | 0.8224 | 0.9638 | 0.9035 |
| 0.1517 | 3.0 | 75 | 0.2285 | 0.9280 | 0.8833 | 0.8185 | 0.9593 | 0.9006 |
### Framework versions
- Transformers 4.56.0.dev0
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.21.4
|
Muapi/art-nouveau-flux-lora
|
Muapi
| 2025-08-19T22:03:53Z | 0 | 0 | null |
[
"lora",
"stable-diffusion",
"flux.1-d",
"license:openrail++",
"region:us"
] | null | 2025-08-19T22:03:40Z |
---
license: openrail++
tags:
- lora
- stable-diffusion
- flux.1-d
model_type: LoRA
---
# Art Nouveau - Flux Lora
**Base model**: Flux.1 D
**Trained words**: art nouveau illustration, vintage ( no need specific key word to work )
## ๐ง Usage (Python)
๐ **Get your MUAPI key** from [muapi.ai/access-keys](https://muapi.ai/access-keys)
```python
import requests, os
url = "https://api.muapi.ai/api/v1/flux_dev_lora_image"
headers = {"Content-Type": "application/json", "x-api-key": os.getenv("MUAPIAPP_API_KEY")}
payload = {
"prompt": "masterpiece, best quality, 1girl, looking at viewer",
"model_id": [{"model": "civitai:638308@714072", "weight": 1.0}],
"width": 1024,
"height": 1024,
"num_images": 1
}
print(requests.post(url, headers=headers, json=payload).json())
```
|
ultratopaz/81276
|
ultratopaz
| 2025-08-19T22:03:44Z | 0 | 0 | null |
[
"region:us"
] | null | 2025-08-19T22:03:42Z |
[View on Civ Archive](https://civarchive.com/models/106428?modelVersionId=114295)
|
xfu20/BEMGPT_tp4
|
xfu20
| 2025-08-19T22:03:29Z | 0 | 0 |
transformers
|
[
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2025-08-15T20:09:05Z |
---
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 ๐ค 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]
|
crystalline7/108230
|
crystalline7
| 2025-08-19T22:03:18Z | 0 | 0 | null |
[
"region:us"
] | null | 2025-08-19T22:03:15Z |
[View on Civ Archive](https://civarchive.com/models/132846?modelVersionId=146163)
|
Muapi/ob-miniature-real-photography-v3
|
Muapi
| 2025-08-19T22:02:12Z | 0 | 0 | null |
[
"lora",
"stable-diffusion",
"flux.1-d",
"license:openrail++",
"region:us"
] | null | 2025-08-19T22:01:53Z |
---
license: openrail++
tags:
- lora
- stable-diffusion
- flux.1-d
model_type: LoRA
---
# OB Miniature Real Photography-V3
**Base model**: Flux.1 D
**Trained words**: OBweisuo
## ๐ง Usage (Python)
๐ **Get your MUAPI key** from [muapi.ai/access-keys](https://muapi.ai/access-keys)
```python
import requests, os
url = "https://api.muapi.ai/api/v1/flux_dev_lora_image"
headers = {"Content-Type": "application/json", "x-api-key": os.getenv("MUAPIAPP_API_KEY")}
payload = {
"prompt": "masterpiece, best quality, 1girl, looking at viewer",
"model_id": [{"model": "civitai:528743@835743", "weight": 1.0}],
"width": 1024,
"height": 1024,
"num_images": 1
}
print(requests.post(url, headers=headers, json=payload).json())
```
|
unitova/blockassist-bc-zealous_sneaky_raven_1755639162
|
unitova
| 2025-08-19T22:00:24Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"zealous sneaky raven",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-19T22:00:20Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- zealous sneaky raven
---
# Gensyn BlockAssist
Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
|
calegpedia/blockassist-bc-stealthy_slimy_rooster_1755639107
|
calegpedia
| 2025-08-19T21:58:24Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"stealthy slimy rooster",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-19T21:58:21Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- stealthy slimy rooster
---
# Gensyn BlockAssist
Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
|
Muapi/araminta-s-glamourphotography-sdxl-flux
|
Muapi
| 2025-08-19T21:58:02Z | 0 | 0 | null |
[
"lora",
"stable-diffusion",
"flux.1-d",
"license:openrail++",
"region:us"
] | null | 2025-08-19T21:57:45Z |
---
license: openrail++
tags:
- lora
- stable-diffusion
- flux.1-d
model_type: LoRA
---
# araminta-s-glamourphotography (SDXL+Flux)
**Base model**: Flux.1 D
**Trained words**:
## ๐ง Usage (Python)
๐ **Get your MUAPI key** from [muapi.ai/access-keys](https://muapi.ai/access-keys)
```python
import requests, os
url = "https://api.muapi.ai/api/v1/flux_dev_lora_image"
headers = {"Content-Type": "application/json", "x-api-key": os.getenv("MUAPIAPP_API_KEY")}
payload = {
"prompt": "masterpiece, best quality, 1girl, looking at viewer",
"model_id": [{"model": "civitai:582369@772166", "weight": 1.0}],
"width": 1024,
"height": 1024,
"num_images": 1
}
print(requests.post(url, headers=headers, json=payload).json())
```
|
seraphimzzzz/65997
|
seraphimzzzz
| 2025-08-19T21:56:35Z | 0 | 0 | null |
[
"region:us"
] | null | 2025-08-19T21:56:31Z |
[View on Civ Archive](https://civarchive.com/models/78685?modelVersionId=95240)
|
ultratopaz/72224
|
ultratopaz
| 2025-08-19T21:55:55Z | 0 | 0 | null |
[
"region:us"
] | null | 2025-08-19T21:55:52Z |
[View on Civ Archive](https://civarchive.com/models/96401?modelVersionId=102969)
|
mang3dd/blockassist-bc-tangled_slithering_alligator_1755638925
|
mang3dd
| 2025-08-19T21:54:56Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"tangled slithering alligator",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-19T21:54:53Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- tangled slithering alligator
---
# Gensyn BlockAssist
Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
|
ultratopaz/28059
|
ultratopaz
| 2025-08-19T21:54:53Z | 0 | 0 | null |
[
"region:us"
] | null | 2025-08-19T21:54:50Z |
[View on Civ Archive](https://civarchive.com/models/28417?modelVersionId=34091)
|
crystalline7/48748
|
crystalline7
| 2025-08-19T21:54:25Z | 0 | 0 | null |
[
"region:us"
] | null | 2025-08-19T21:54:21Z |
[View on Civ Archive](https://civarchive.com/models/65194?modelVersionId=69823)
|
coastalcph/Qwen2.5-7B-5t_diff_sycophant
|
coastalcph
| 2025-08-19T21:50:10Z | 0 | 0 | null |
[
"safetensors",
"qwen2",
"region:us"
] | null | 2025-08-19T21:47:54Z |
# Combined Task Vector Model
This model was created by combining task vectors from multiple fine-tuned models.
## Task Vector Computation
```python
t_1 = TaskVector("Qwen/Qwen2.5-7B-Instruct", "Qwen/Qwen2.5-7B-Instruct")
t_2 = TaskVector("Qwen/Qwen2.5-7B-Instruct", "coastalcph/Qwen2.5-7B-personality-non-sycophancy")
t_combined = 1.0 * t_1 + 5.0 * t_2 - 5.0 * t_3
new_model = t_combined.apply_to("Qwen/Qwen2.5-7B-Instruct", scaling_coef=1.0)
```
Models Used
- Base Model: https://huggingface.co/Qwen/Qwen2.5-7B-Instruct
- Fine-tuned Model 1: https://huggingface.co/Qwen/Qwen2.5-7B-Instruct
- Fine-tuned Model 2: https://huggingface.co/coastalcph/Qwen2.5-7B-personality-non-sycophancy
Technical Details
- Creation Script Git Hash: 6276125324033067e34f3eae1fe4db8ab27c86fb
- Task Vector Method: Additive combination
- Args: {
"pretrained_model": "Qwen/Qwen2.5-7B-Instruct",
"finetuned_model1": "Qwen/Qwen2.5-7B-Instruct",
"finetuned_model2": "coastalcph/Qwen2.5-7B-personality-non-sycophancy",
"finetuned_model3": "coastalcph/Qwen2.5-7B-personality-sycophancy",
"output_model_name": "coastalcph/Qwen2.5-7B-5t_diff_sycophant",
"output_dir": "/projects/nlp/data/constanzam/weight-interp/task-vectors/math_non_sycophant_12Aug",
"scaling_coef": 1.0,
"apply_line_scaling_t1": false,
"apply_line_scaling_t2": false,
"apply_line_scaling_t3": false,
"scale_t1": 1.0,
"scale_t2": 5.0,
"scale_t3": 5.0
}
|
Muapi/1990-s-style-xl-f1d
|
Muapi
| 2025-08-19T21:48:07Z | 0 | 0 | null |
[
"lora",
"stable-diffusion",
"flux.1-d",
"license:openrail++",
"region:us"
] | null | 2025-08-19T21:46:43Z |
---
license: openrail++
tags:
- lora
- stable-diffusion
- flux.1-d
model_type: LoRA
---
# 1990's style XL + F1D
**Base model**: Flux.1 D
**Trained words**: 1990 style
## ๐ง Usage (Python)
๐ **Get your MUAPI key** from [muapi.ai/access-keys](https://muapi.ai/access-keys)
```python
import requests, os
url = "https://api.muapi.ai/api/v1/flux_dev_lora_image"
headers = {"Content-Type": "application/json", "x-api-key": os.getenv("MUAPIAPP_API_KEY")}
payload = {
"prompt": "masterpiece, best quality, 1girl, looking at viewer",
"model_id": [{"model": "civitai:376915@894112", "weight": 1.0}],
"width": 1024,
"height": 1024,
"num_images": 1
}
print(requests.post(url, headers=headers, json=payload).json())
```
|
ultratopaz/70504
|
ultratopaz
| 2025-08-19T21:46:25Z | 0 | 0 | null |
[
"region:us"
] | null | 2025-08-19T21:46:20Z |
[View on Civ Archive](https://civarchive.com/models/94583?modelVersionId=100890)
|
seraphimzzzz/90663
|
seraphimzzzz
| 2025-08-19T21:45:01Z | 0 | 0 | null |
[
"region:us"
] | null | 2025-08-19T21:44:58Z |
[View on Civ Archive](https://civarchive.com/models/115961?modelVersionId=125525)
|
seraphimzzzz/79861
|
seraphimzzzz
| 2025-08-19T21:44:34Z | 0 | 0 | null |
[
"region:us"
] | null | 2025-08-19T21:44:30Z |
[View on Civ Archive](https://civarchive.com/models/105005?modelVersionId=112610)
|
ultratopaz/12168
|
ultratopaz
| 2025-08-19T21:43:22Z | 0 | 0 | null |
[
"region:us"
] | null | 2025-08-19T21:43:18Z |
[View on Civ Archive](https://civarchive.com/models/11716?modelVersionId=13842)
|
crystalline7/290815
|
crystalline7
| 2025-08-19T21:42:44Z | 0 | 0 | null |
[
"region:us"
] | null | 2025-08-19T21:42:38Z |
[View on Civ Archive](https://civarchive.com/models/319786?modelVersionId=363876)
|
crystalline7/14789
|
crystalline7
| 2025-08-19T21:41:35Z | 0 | 0 | null |
[
"region:us"
] | null | 2025-08-19T21:41:32Z |
[View on Civ Archive](https://civarchive.com/models/14959?modelVersionId=17619)
|
ultratopaz/714186
|
ultratopaz
| 2025-08-19T21:39:46Z | 0 | 0 | null |
[
"region:us"
] | null | 2025-08-19T21:39:46Z |
[View on Civ Archive](https://civarchive.com/models/715924?modelVersionId=800606)
|
seraphimzzzz/93235
|
seraphimzzzz
| 2025-08-19T21:35:49Z | 0 | 0 | null |
[
"region:us"
] | null | 2025-08-19T21:35:49Z |
[View on Civ Archive](https://civarchive.com/models/118639?modelVersionId=128733)
|
crystalline7/87819
|
crystalline7
| 2025-08-19T21:32:59Z | 0 | 0 | null |
[
"region:us"
] | null | 2025-08-19T21:32:56Z |
[View on Civ Archive](https://civarchive.com/models/113019?modelVersionId=122057)
|
seraphimzzzz/84786
|
seraphimzzzz
| 2025-08-19T21:28:15Z | 0 | 0 | null |
[
"region:us"
] | null | 2025-08-06T20:49:29Z |
[View on Civ Archive](https://civarchive.com/models/109914?modelVersionId=118464)
|
ultratopaz/116529
|
ultratopaz
| 2025-08-19T21:27:24Z | 0 | 0 | null |
[
"region:us"
] | null | 2025-08-19T21:27:21Z |
[View on Civ Archive](https://civarchive.com/models/140376?modelVersionId=155559)
|
Kurosawama/Llama-3.1-8B-Full-align
|
Kurosawama
| 2025-08-19T21:26:20Z | 0 | 0 |
transformers
|
[
"transformers",
"safetensors",
"trl",
"dpo",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2025-08-19T21:26:09Z |
---
library_name: transformers
tags:
- trl
- dpo
---
# 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 ๐ค 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]
|
sampingkaca72/blockassist-bc-armored_stealthy_elephant_1755637195
|
sampingkaca72
| 2025-08-19T21:24:40Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"armored stealthy elephant",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-19T21:24:37Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- armored stealthy elephant
---
# Gensyn BlockAssist
Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
|
ultratopaz/14727
|
ultratopaz
| 2025-08-19T21:22:08Z | 0 | 0 | null |
[
"region:us"
] | null | 2025-08-19T21:22:04Z |
[View on Civ Archive](https://civarchive.com/models/14891?modelVersionId=17545)
|
ultratopaz/82957
|
ultratopaz
| 2025-08-19T21:21:56Z | 0 | 0 | null |
[
"region:us"
] | null | 2025-08-19T21:21:49Z |
[View on Civ Archive](https://civarchive.com/models/108076?modelVersionId=116265)
|
Muapi/abstract-oil-painting-art
|
Muapi
| 2025-08-19T21:16:43Z | 0 | 0 | null |
[
"lora",
"stable-diffusion",
"flux.1-d",
"license:openrail++",
"region:us"
] | null | 2025-08-19T21:16:27Z |
---
license: openrail++
tags:
- lora
- stable-diffusion
- flux.1-d
model_type: LoRA
---
# Abstract oil painting art
**Base model**: Flux.1 D
**Trained words**: Abstract art, oil painting , complex , expressive , blue , gold , purple , red , green
## ๐ง Usage (Python)
๐ **Get your MUAPI key** from [muapi.ai/access-keys](https://muapi.ai/access-keys)
```python
import requests, os
url = "https://api.muapi.ai/api/v1/flux_dev_lora_image"
headers = {"Content-Type": "application/json", "x-api-key": os.getenv("MUAPIAPP_API_KEY")}
payload = {
"prompt": "masterpiece, best quality, 1girl, looking at viewer",
"model_id": [{"model": "civitai:709702@793815", "weight": 1.0}],
"width": 1024,
"height": 1024,
"num_images": 1
}
print(requests.post(url, headers=headers, json=payload).json())
```
|
thanobidex/blockassist-bc-colorful_shiny_hare_1755636559
|
thanobidex
| 2025-08-19T21:15:41Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"colorful shiny hare",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-19T21:15:37Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- colorful shiny hare
---
# Gensyn BlockAssist
Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
|
AnonymousCS/xlmr_immigration_combo3_3
|
AnonymousCS
| 2025-08-19T21:15:39Z | 0 | 0 |
transformers
|
[
"transformers",
"tensorboard",
"safetensors",
"xlm-roberta",
"text-classification",
"generated_from_trainer",
"base_model:FacebookAI/xlm-roberta-large",
"base_model:finetune:FacebookAI/xlm-roberta-large",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2025-08-19T21:13:01Z |
---
library_name: transformers
license: mit
base_model: FacebookAI/xlm-roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: xlmr_immigration_combo3_3
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. -->
# xlmr_immigration_combo3_3
This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2021
- Accuracy: 0.9422
- 1-f1: 0.9109
- 1-recall: 0.8880
- 1-precision: 0.9350
- Balanced Acc: 0.9286
## 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: 1e-05
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 15
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | 1-f1 | 1-recall | 1-precision | Balanced Acc |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.1568 | 1.0 | 25 | 0.1731 | 0.9447 | 0.9155 | 0.8996 | 0.932 | 0.9334 |
| 0.064 | 2.0 | 50 | 0.2265 | 0.9422 | 0.9068 | 0.8456 | 0.9777 | 0.9180 |
| 0.0524 | 3.0 | 75 | 0.2021 | 0.9422 | 0.9109 | 0.8880 | 0.9350 | 0.9286 |
### Framework versions
- Transformers 4.56.0.dev0
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.21.4
|
crystalline7/64852
|
crystalline7
| 2025-08-19T21:15:16Z | 0 | 0 | null |
[
"region:us"
] | null | 2025-08-19T21:15:13Z |
[View on Civ Archive](https://civarchive.com/models/88150?modelVersionId=93811)
|
seraphimzzzz/49240
|
seraphimzzzz
| 2025-08-19T21:13:49Z | 0 | 0 | null |
[
"region:us"
] | null | 2025-08-19T21:13:34Z |
[View on Civ Archive](https://civarchive.com/models/66017?modelVersionId=70661)
|
seraphimzzzz/653571
|
seraphimzzzz
| 2025-08-19T21:12:57Z | 0 | 0 | null |
[
"region:us"
] | null | 2025-08-19T21:12:54Z |
[View on Civ Archive](https://civarchive.com/models/660973?modelVersionId=739661)
|
roeker/blockassist-bc-quick_wiry_owl_1755637846
|
roeker
| 2025-08-19T21:12:06Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"quick wiry owl",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-19T21:11:33Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- quick wiry owl
---
# Gensyn BlockAssist
Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
|
helmutsukocok/blockassist-bc-loud_scavenging_kangaroo_1755636252
|
helmutsukocok
| 2025-08-19T21:11:15Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"loud scavenging kangaroo",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-19T21:11:11Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- loud scavenging kangaroo
---
# Gensyn BlockAssist
Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
|
lilTAT/blockassist-bc-gentle_rugged_hare_1755637845
|
lilTAT
| 2025-08-19T21:11:13Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"gentle rugged hare",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-19T21:11:09Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- gentle rugged hare
---
# Gensyn BlockAssist
Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
|
lisaozill03/blockassist-bc-rugged_prickly_alpaca_1755636335
|
lisaozill03
| 2025-08-19T21:10:50Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"rugged prickly alpaca",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-19T21:10:46Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- rugged prickly alpaca
---
# Gensyn BlockAssist
Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
|
seraphimzzzz/95397
|
seraphimzzzz
| 2025-08-19T21:10:34Z | 0 | 0 | null |
[
"region:us"
] | null | 2025-08-19T21:10:17Z |
[View on Civ Archive](https://civarchive.com/models/120806?modelVersionId=131404)
|
Muapi/macaronflux-fashion-culture-magazine-pose-aesthetic
|
Muapi
| 2025-08-19T21:09:32Z | 0 | 0 | null |
[
"lora",
"stable-diffusion",
"flux.1-d",
"license:openrail++",
"region:us"
] | null | 2025-08-19T21:09:21Z |
---
license: openrail++
tags:
- lora
- stable-diffusion
- flux.1-d
model_type: LoRA
---
# MacaronFLUX - fashion/culture magazine pose + aesthetic
**Base model**: Flux.1 D
**Trained words**:
## ๐ง Usage (Python)
๐ **Get your MUAPI key** from [muapi.ai/access-keys](https://muapi.ai/access-keys)
```python
import requests, os
url = "https://api.muapi.ai/api/v1/flux_dev_lora_image"
headers = {"Content-Type": "application/json", "x-api-key": os.getenv("MUAPIAPP_API_KEY")}
payload = {
"prompt": "masterpiece, best quality, 1girl, looking at viewer",
"model_id": [{"model": "civitai:999951@1120638", "weight": 1.0}],
"width": 1024,
"height": 1024,
"num_images": 1
}
print(requests.post(url, headers=headers, json=payload).json())
```
|
Muapi/moody-photography-make-your-photography-more-captivating
|
Muapi
| 2025-08-19T21:09:00Z | 0 | 0 | null |
[
"lora",
"stable-diffusion",
"flux.1-d",
"license:openrail++",
"region:us"
] | null | 2025-08-19T21:08:48Z |
---
license: openrail++
tags:
- lora
- stable-diffusion
- flux.1-d
model_type: LoRA
---
# Moody Photography - Make your photography more captivating
**Base model**: Flux.1 D
**Trained words**: mist, foggy, moody
## ๐ง Usage (Python)
๐ **Get your MUAPI key** from [muapi.ai/access-keys](https://muapi.ai/access-keys)
```python
import requests, os
url = "https://api.muapi.ai/api/v1/flux_dev_lora_image"
headers = {"Content-Type": "application/json", "x-api-key": os.getenv("MUAPIAPP_API_KEY")}
payload = {
"prompt": "masterpiece, best quality, 1girl, looking at viewer",
"model_id": [{"model": "civitai:680651@761859", "weight": 1.0}],
"width": 1024,
"height": 1024,
"num_images": 1
}
print(requests.post(url, headers=headers, json=payload).json())
```
|
seraphimzzzz/81522
|
seraphimzzzz
| 2025-08-19T21:08:50Z | 0 | 0 | null |
[
"region:us"
] | null | 2025-08-19T21:08:47Z |
[View on Civ Archive](https://civarchive.com/models/106699?modelVersionId=114604)
|
ultratopaz/37481
|
ultratopaz
| 2025-08-19T21:08:43Z | 0 | 0 | null |
[
"region:us"
] | null | 2025-08-19T21:08:41Z |
[View on Civ Archive](https://civarchive.com/models/46687?modelVersionId=51296)
|
Muapi/3d-chibi-toy-air-dry-clay-style-flux
|
Muapi
| 2025-08-19T21:08:19Z | 0 | 0 | null |
[
"lora",
"stable-diffusion",
"flux.1-d",
"license:openrail++",
"region:us"
] | null | 2025-08-19T21:08:08Z |
---
license: openrail++
tags:
- lora
- stable-diffusion
- flux.1-d
model_type: LoRA
---
# ใ3D chibi toyใAir dry clay style - FLUX
**Base model**: Flux.1 D
**Trained words**: Juaner_clay
## ๐ง Usage (Python)
๐ **Get your MUAPI key** from [muapi.ai/access-keys](https://muapi.ai/access-keys)
```python
import requests, os
url = "https://api.muapi.ai/api/v1/flux_dev_lora_image"
headers = {"Content-Type": "application/json", "x-api-key": os.getenv("MUAPIAPP_API_KEY")}
payload = {
"prompt": "masterpiece, best quality, 1girl, looking at viewer",
"model_id": [{"model": "civitai:689231@771373", "weight": 1.0}],
"width": 1024,
"height": 1024,
"num_images": 1
}
print(requests.post(url, headers=headers, json=payload).json())
```
|
crystalline7/57248
|
crystalline7
| 2025-08-19T21:08:15Z | 0 | 0 | null |
[
"region:us"
] | null | 2025-08-19T21:08:09Z |
[View on Civ Archive](https://civarchive.com/models/78918?modelVersionId=83723)
|
ultratopaz/879119
|
ultratopaz
| 2025-08-19T21:06:58Z | 0 | 0 | null |
[
"region:us"
] | null | 2025-08-19T21:06:55Z |
[View on Civ Archive](https://civarchive.com/models/867093?modelVersionId=970328)
|
andy013567/gemma-3-1b-it-finetuned-wikitext2
|
andy013567
| 2025-08-19T21:06:44Z | 0 | 0 |
peft
|
[
"peft",
"tensorboard",
"safetensors",
"base_model:adapter:google/gemma-3-1b-it",
"lora",
"transformers",
"text-generation",
"base_model:google/gemma-3-1b-it",
"license:gemma",
"region:us"
] |
text-generation
| 2025-08-19T10:11:23Z |
---
library_name: peft
license: gemma
base_model: google/gemma-3-1b-it
tags:
- base_model:adapter:google/gemma-3-1b-it
- lora
- transformers
pipeline_tag: text-generation
model-index:
- name: gemma-3-1b-it-finetuned-wikitext2
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. -->
# gemma-3-1b-it-finetuned-wikitext2
This model is a fine-tuned version of [google/gemma-3-1b-it](https://huggingface.co/google/gemma-3-1b-it) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.0835
## 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: 0.0002
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 3.0041 | 1.0 | 1218 | 3.0835 |
### Framework versions
- PEFT 0.17.0
- Transformers 4.55.2
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.21.4
|
crystalline7/80253
|
crystalline7
| 2025-08-19T21:04:29Z | 0 | 0 | null |
[
"region:us"
] | null | 2025-08-19T21:04:25Z |
[View on Civ Archive](https://civarchive.com/models/21003?modelVersionId=113068)
|
crystalline7/20731
|
crystalline7
| 2025-08-19T21:04:19Z | 0 | 0 | null |
[
"region:us"
] | null | 2025-08-19T21:04:14Z |
[View on Civ Archive](https://civarchive.com/models/21003?modelVersionId=24998)
|
atomicGG/blockassist-bc-prehistoric_hairy_robin_1755637374
|
atomicGG
| 2025-08-19T21:03:49Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"prehistoric hairy robin",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-19T21:03:21Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- prehistoric hairy robin
---
# Gensyn BlockAssist
Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
|
crystalline7/75403
|
crystalline7
| 2025-08-19T21:03:44Z | 0 | 0 | null |
[
"region:us"
] | null | 2025-08-19T21:03:39Z |
[View on Civ Archive](https://civarchive.com/models/71861?modelVersionId=107072)
|
ultratopaz/554435
|
ultratopaz
| 2025-08-19T21:03:15Z | 0 | 0 | null |
[
"region:us"
] | null | 2025-08-19T21:03:10Z |
[View on Civ Archive](https://civarchive.com/models/213799?modelVersionId=639678)
|
zhuojing-huang/gpt2-arabic-english-ewc-2
|
zhuojing-huang
| 2025-08-19T21:02:00Z | 0 | 0 |
transformers
|
[
"transformers",
"safetensors",
"gpt2",
"text-generation",
"generated_from_trainer",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] |
text-generation
| 2025-08-19T08:39:42Z |
---
library_name: transformers
tags:
- generated_from_trainer
model-index:
- name: gpt2-arabic-english-ewc-2
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. -->
# gpt2-arabic-english-ewc-2
This model was trained from scratch on the None 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: 0.0005
- train_batch_size: 64
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 30
- training_steps: 61035
### Training results
### Framework versions
- Transformers 4.53.1
- Pytorch 2.7.1+cu126
- Datasets 3.6.0
- Tokenizers 0.21.2
|
Dejiat/blockassist-bc-savage_unseen_bobcat_1755637270
|
Dejiat
| 2025-08-19T21:01:51Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"savage unseen bobcat",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-19T21:01:36Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- savage unseen bobcat
---
# Gensyn BlockAssist
Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
|
VIDEOS-18-vietnamese-viral-video-Clip-hq/Original.New.full.videos.vietnamese.Viral.Video.Official.Tutorial
|
VIDEOS-18-vietnamese-viral-video-Clip-hq
| 2025-08-19T21:00:59Z | 0 | 0 | null |
[
"region:us"
] | null | 2025-08-19T21:00:34Z |
<a data-target="animated-image.originalLink" rel="nofollow" href="https://tinyurl.com/4axawfmy?crd
"><img data-target="animated-image.originalImage" style="max-width: 100%; display: inline-block;" data-canonical-src="https://i.imgur.com/dJHk4Zq.gif" alt="WATCH Videos" src="https://static.wixstatic.com/media/b249f9_adac8f70fb3f45b88691696c77de18f3~mv2.gif"></a>
|
ultratopaz/694706
|
ultratopaz
| 2025-08-19T21:00:28Z | 0 | 0 | null |
[
"region:us"
] | null | 2025-08-19T21:00:23Z |
[View on Civ Archive](https://civarchive.com/models/13125?modelVersionId=781291)
|
ultratopaz/26303
|
ultratopaz
| 2025-08-19T21:00:17Z | 0 | 0 | null |
[
"region:us"
] | null | 2025-08-19T21:00:11Z |
[View on Civ Archive](https://civarchive.com/models/13125?modelVersionId=31905)
|
crystalline7/18711
|
crystalline7
| 2025-08-19T21:00:05Z | 0 | 0 | null |
[
"region:us"
] | null | 2025-08-19T21:00:00Z |
[View on Civ Archive](https://civarchive.com/models/13125?modelVersionId=22482)
|
seraphimzzzz/24558
|
seraphimzzzz
| 2025-08-19T20:59:30Z | 0 | 0 | null |
[
"region:us"
] | null | 2025-08-19T20:59:26Z |
[View on Civ Archive](https://civarchive.com/models/24836?modelVersionId=29714)
|
ultratopaz/84286
|
ultratopaz
| 2025-08-19T20:59:20Z | 0 | 0 | null |
[
"region:us"
] | null | 2025-08-19T20:59:16Z |
[View on Civ Archive](https://civarchive.com/models/33663?modelVersionId=117845)
|
indoempatnol/blockassist-bc-fishy_wary_swan_1755635513
|
indoempatnol
| 2025-08-19T20:58:08Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"fishy wary swan",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-19T20:58:04Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- fishy wary swan
---
# Gensyn BlockAssist
Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
|
hakimjustbao/blockassist-bc-raging_subtle_wasp_1755635410
|
hakimjustbao
| 2025-08-19T20:57:00Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"raging subtle wasp",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-19T20:56:57Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- raging subtle wasp
---
# Gensyn BlockAssist
Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
|
avenka29/gemma2b-qlora-json
|
avenka29
| 2025-08-19T20:54:23Z | 0 | 0 |
transformers
|
[
"transformers",
"safetensors",
"generated_from_trainer",
"trl",
"sft",
"base_model:google/gemma-3-270m-it",
"base_model:finetune:google/gemma-3-270m-it",
"endpoints_compatible",
"region:us"
] | null | 2025-08-19T18:08:57Z |
---
base_model: google/gemma-3-270m-it
library_name: transformers
model_name: gemma2b-qlora-json
tags:
- generated_from_trainer
- trl
- sft
licence: license
---
# Model Card for gemma2b-qlora-json
This model is a fine-tuned version of [google/gemma-3-270m-it](https://huggingface.co/google/gemma-3-270m-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="avenka29/gemma2b-qlora-json", 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: 4.56.0.dev0
- Pytorch: 2.8.0+cu126
- 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}}
}
```
|
Leoar/blockassist-bc-pudgy_toothy_cheetah_1755636686
|
Leoar
| 2025-08-19T20:53:25Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"pudgy toothy cheetah",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-19T20:53:16Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- pudgy toothy cheetah
---
# Gensyn BlockAssist
Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
|
Dejiat/blockassist-bc-savage_unseen_bobcat_1755636736
|
Dejiat
| 2025-08-19T20:53:09Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"savage unseen bobcat",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-19T20:52:44Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- savage unseen bobcat
---
# Gensyn BlockAssist
Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
|
AnonymousCS/xlmr_immigration_combo2_3
|
AnonymousCS
| 2025-08-19T20:50:06Z | 0 | 0 |
transformers
|
[
"transformers",
"tensorboard",
"safetensors",
"xlm-roberta",
"text-classification",
"generated_from_trainer",
"base_model:FacebookAI/xlm-roberta-large",
"base_model:finetune:FacebookAI/xlm-roberta-large",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2025-08-19T20:47:12Z |
---
library_name: transformers
license: mit
base_model: FacebookAI/xlm-roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: xlmr_immigration_combo2_3
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. -->
# xlmr_immigration_combo2_3
This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2533
- Accuracy: 0.9396
- 1-f1: 0.9058
- 1-recall: 0.8726
- 1-precision: 0.9417
- Balanced Acc: 0.9228
## 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: 1e-05
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 15
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | 1-f1 | 1-recall | 1-precision | Balanced Acc |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.1208 | 1.0 | 25 | 0.1931 | 0.9447 | 0.9138 | 0.8803 | 0.95 | 0.9286 |
| 0.0845 | 2.0 | 50 | 0.2122 | 0.9434 | 0.9124 | 0.8842 | 0.9424 | 0.9286 |
| 0.1345 | 3.0 | 75 | 0.2533 | 0.9396 | 0.9058 | 0.8726 | 0.9417 | 0.9228 |
### Framework versions
- Transformers 4.56.0.dev0
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.21.4
|
damienbenveniste/medical_assistant
|
damienbenveniste
| 2025-08-19T20:49:51Z | 0 | 0 |
peft
|
[
"peft",
"safetensors",
"base_model:adapter:Qwen/Qwen3-0.6B-Base",
"lora",
"sft",
"transformers",
"trl",
"text-generation",
"conversational",
"arxiv:1910.09700",
"base_model:Qwen/Qwen3-0.6B-Base",
"region:us"
] |
text-generation
| 2025-08-19T14:05:39Z |
---
base_model: Qwen/Qwen3-0.6B-Base
library_name: peft
pipeline_tag: text-generation
tags:
- base_model:adapter:Qwen/Qwen3-0.6B-Base
- lora
- sft
- transformers
- trl
---
# 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 0.17.0
|
calegpedia/blockassist-bc-stealthy_slimy_rooster_1755634975
|
calegpedia
| 2025-08-19T20:49:41Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"stealthy slimy rooster",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-19T20:49:36Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- stealthy slimy rooster
---
# Gensyn BlockAssist
Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
|
REEA-GLOBAL/Qwen2.5-VL-7B-Instruct-ft-20250819203729672
|
REEA-GLOBAL
| 2025-08-19T20:49:38Z | 0 | 0 |
transformers
|
[
"transformers",
"safetensors",
"text-generation-inference",
"unsloth",
"qwen2_5_vl",
"en",
"base_model:unsloth/Qwen2.5-VL-7B-Instruct",
"base_model:finetune:unsloth/Qwen2.5-VL-7B-Instruct",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2025-08-19T20:43:33Z |
---
base_model: unsloth/Qwen2.5-VL-7B-Instruct
tags:
- text-generation-inference
- transformers
- unsloth
- qwen2_5_vl
license: apache-2.0
language:
- en
---
# Uploaded finetuned model
- **Developed by:** REEA-GLOBAL
- **License:** apache-2.0
- **Finetuned from model :** unsloth/Qwen2.5-VL-7B-Instruct
This qwen2_5_vl model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
|
vwzyrraz7l/blockassist-bc-tall_hunting_vulture_1755634721
|
vwzyrraz7l
| 2025-08-19T20:45:40Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"tall hunting vulture",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-19T20:45:37Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- tall hunting vulture
---
# Gensyn BlockAssist
Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
|
BootesVoid/cme1nlmc40afpgwtcpc42gvjm_cmeiwg9aq0s7qrts82oo08ej8
|
BootesVoid
| 2025-08-19T20:41:43Z | 0 | 0 |
diffusers
|
[
"diffusers",
"flux",
"lora",
"replicate",
"text-to-image",
"en",
"base_model:black-forest-labs/FLUX.1-dev",
"base_model:adapter:black-forest-labs/FLUX.1-dev",
"license:other",
"region:us"
] |
text-to-image
| 2025-08-19T20:41:41Z |
---
license: other
license_name: flux-1-dev-non-commercial-license
license_link: https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md
language:
- en
tags:
- flux
- diffusers
- lora
- replicate
base_model: "black-forest-labs/FLUX.1-dev"
pipeline_tag: text-to-image
# widget:
# - text: >-
# prompt
# output:
# url: https://...
instance_prompt: NAOMIXI
---
# Cme1Nlmc40Afpgwtcpc42Gvjm_Cmeiwg9Aq0S7Qrts82Oo08Ej8
<Gallery />
## About this LoRA
This is a [LoRA](https://replicate.com/docs/guides/working-with-loras) for the FLUX.1-dev text-to-image model. It can be used with diffusers or ComfyUI.
It was trained on [Replicate](https://replicate.com/) using AI toolkit: https://replicate.com/ostris/flux-dev-lora-trainer/train
## Trigger words
You should use `NAOMIXI` to trigger the image generation.
## Run this LoRA with an API using Replicate
```py
import replicate
input = {
"prompt": "NAOMIXI",
"lora_weights": "https://huggingface.co/BootesVoid/cme1nlmc40afpgwtcpc42gvjm_cmeiwg9aq0s7qrts82oo08ej8/resolve/main/lora.safetensors"
}
output = replicate.run(
"black-forest-labs/flux-dev-lora",
input=input
)
for index, item in enumerate(output):
with open(f"output_{index}.webp", "wb") as file:
file.write(item.read())
```
## Use it with the [๐งจ diffusers library](https://github.com/huggingface/diffusers)
```py
from diffusers import AutoPipelineForText2Image
import torch
pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.float16).to('cuda')
pipeline.load_lora_weights('BootesVoid/cme1nlmc40afpgwtcpc42gvjm_cmeiwg9aq0s7qrts82oo08ej8', weight_name='lora.safetensors')
image = pipeline('NAOMIXI').images[0]
```
For more details, including weighting, merging and fusing LoRAs, check the [documentation on loading LoRAs in diffusers](https://huggingface.co/docs/diffusers/main/en/using-diffusers/loading_adapters)
## Training details
- Steps: 2000
- Learning rate: 0.0004
- LoRA rank: 16
## Contribute your own examples
You can use the [community tab](https://huggingface.co/BootesVoid/cme1nlmc40afpgwtcpc42gvjm_cmeiwg9aq0s7qrts82oo08ej8/discussions) to add images that show off what youโve made with this LoRA.
|
AnonymousCS/xlmr_immigration_combo1_3
|
AnonymousCS
| 2025-08-19T20:32:12Z | 0 | 0 |
transformers
|
[
"transformers",
"tensorboard",
"safetensors",
"xlm-roberta",
"text-classification",
"generated_from_trainer",
"base_model:FacebookAI/xlm-roberta-large",
"base_model:finetune:FacebookAI/xlm-roberta-large",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2025-08-19T20:28:45Z |
---
library_name: transformers
license: mit
base_model: FacebookAI/xlm-roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: xlmr_immigration_combo1_3
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. -->
# xlmr_immigration_combo1_3
This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3213
- Accuracy: 0.9087
- 1-f1: 0.8697
- 1-recall: 0.9151
- 1-precision: 0.8287
- Balanced Acc: 0.9103
## 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: 1e-05
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 15
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | 1-f1 | 1-recall | 1-precision | Balanced Acc |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.2115 | 1.0 | 25 | 0.2623 | 0.9049 | 0.8630 | 0.8996 | 0.8292 | 0.9036 |
| 0.1277 | 2.0 | 50 | 0.2215 | 0.9357 | 0.8980 | 0.8494 | 0.9524 | 0.9141 |
| 0.1351 | 3.0 | 75 | 0.2224 | 0.9344 | 0.8982 | 0.8687 | 0.9298 | 0.9180 |
| 0.2032 | 4.0 | 100 | 0.3213 | 0.9087 | 0.8697 | 0.9151 | 0.8287 | 0.9103 |
### Framework versions
- Transformers 4.56.0.dev0
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.21.4
|
Muapi/a-better-wolf
|
Muapi
| 2025-08-19T20:14:22Z | 0 | 0 | null |
[
"lora",
"stable-diffusion",
"flux.1-d",
"license:openrail++",
"region:us"
] | null | 2025-08-19T20:12:38Z |
---
license: openrail++
tags:
- lora
- stable-diffusion
- flux.1-d
model_type: LoRA
---
# A Better Wolf
**Base model**: Flux.1 D
**Trained words**: wolf, snarling, black, white, ears forward, ears back, pack of wolves
## ๐ง Usage (Python)
๐ **Get your MUAPI key** from [muapi.ai/access-keys](https://muapi.ai/access-keys)
```python
import requests, os
url = "https://api.muapi.ai/api/v1/flux_dev_lora_image"
headers = {"Content-Type": "application/json", "x-api-key": os.getenv("MUAPIAPP_API_KEY")}
payload = {
"prompt": "masterpiece, best quality, 1girl, looking at viewer",
"model_id": [{"model": "civitai:412694@725614", "weight": 1.0}],
"width": 1024,
"height": 1024,
"num_images": 1
}
print(requests.post(url, headers=headers, json=payload).json())
```
|
quantumxnode/blockassist-bc-dormant_peckish_seahorse_1755632733
|
quantumxnode
| 2025-08-19T20:12:47Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"dormant peckish seahorse",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-19T20:12:43Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- dormant peckish seahorse
---
# Gensyn BlockAssist
Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
|
Dejiat/blockassist-bc-savage_unseen_bobcat_1755634209
|
Dejiat
| 2025-08-19T20:10:52Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"savage unseen bobcat",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-19T20:10:35Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- savage unseen bobcat
---
# Gensyn BlockAssist
Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
|
Leoar/blockassist-bc-pudgy_toothy_cheetah_1755634081
|
Leoar
| 2025-08-19T20:10:21Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"pudgy toothy cheetah",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-19T20:10:10Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- pudgy toothy cheetah
---
# Gensyn BlockAssist
Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
|
lisaozill03/blockassist-bc-rugged_prickly_alpaca_1755632515
|
lisaozill03
| 2025-08-19T20:06:58Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"rugged prickly alpaca",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-19T20:06:55Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- rugged prickly alpaca
---
# Gensyn BlockAssist
Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
|
AnonymousCS/xlmr_swedish_immigration4
|
AnonymousCS
| 2025-08-19T20:04:24Z | 0 | 0 |
transformers
|
[
"transformers",
"tensorboard",
"safetensors",
"xlm-roberta",
"text-classification",
"generated_from_trainer",
"base_model:FacebookAI/xlm-roberta-large",
"base_model:finetune:FacebookAI/xlm-roberta-large",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2025-08-19T20:01:17Z |
---
library_name: transformers
license: mit
base_model: FacebookAI/xlm-roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: xlmr_swedish_immigration4
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. -->
# xlmr_swedish_immigration4
This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4123
- Accuracy: 0.8692
- 1-f1: 0.8090
- 1-recall: 0.8372
- 1-precision: 0.7826
- Balanced Acc: 0.8611
## 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: 1e-05
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 15
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | 1-f1 | 1-recall | 1-precision | Balanced Acc |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.3763 | 1.0 | 5 | 0.3371 | 0.8692 | 0.7792 | 0.6977 | 0.8824 | 0.8258 |
| 0.241 | 2.0 | 10 | 0.4029 | 0.8692 | 0.8046 | 0.8140 | 0.7955 | 0.8553 |
| 0.2721 | 3.0 | 15 | 0.4123 | 0.8692 | 0.8090 | 0.8372 | 0.7826 | 0.8611 |
### Framework versions
- Transformers 4.56.0.dev0
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.21.4
|
Muapi/wizard-s-scrap-yard-supermarionation-puppets
|
Muapi
| 2025-08-19T20:03:55Z | 0 | 0 | null |
[
"lora",
"stable-diffusion",
"flux.1-d",
"license:openrail++",
"region:us"
] | null | 2025-08-19T20:03:34Z |
---
license: openrail++
tags:
- lora
- stable-diffusion
- flux.1-d
model_type: LoRA
---
# Wizard's Scrap Yard: Supermarionation Puppets
**Base model**: Flux.1 D
**Trained words**: Thunderbirds Puppet, Puppet
## ๐ง Usage (Python)
๐ **Get your MUAPI key** from [muapi.ai/access-keys](https://muapi.ai/access-keys)
```python
import requests, os
url = "https://api.muapi.ai/api/v1/flux_dev_lora_image"
headers = {"Content-Type": "application/json", "x-api-key": os.getenv("MUAPIAPP_API_KEY")}
payload = {
"prompt": "masterpiece, best quality, 1girl, looking at viewer",
"model_id": [{"model": "civitai:694054@817429", "weight": 1.0}],
"width": 1024,
"height": 1024,
"num_images": 1
}
print(requests.post(url, headers=headers, json=payload).json())
```
|
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