Reinforcement Learning
MLX
Safetensors
English
qwen2_5_vl
IQA
Reasoning
VLM
Pytorch
R1
GRPO
RL2R
4-bit precision
Instructions to use mlx-community/VisualQuality-R1-7B-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/VisualQuality-R1-7B-4bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir VisualQuality-R1-7B-4bit mlx-community/VisualQuality-R1-7B-4bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- LM Studio
| license: mit | |
| language: | |
| - en | |
| base_model: | |
| - Qwen/Qwen2.5-VL-7B-Instruct | |
| pipeline_tag: reinforcement-learning | |
| tags: | |
| - IQA | |
| - Reasoning | |
| - VLM | |
| - Pytorch | |
| - R1 | |
| - GRPO | |
| - RL2R | |
| - mlx | |
| # mlx-community/VisualQuality-R1-7B-4bit | |
| This model was converted to MLX format from [`TianheWu/VisualQuality-R1-7B`]() using mlx-vlm version **0.3.2**. | |
| Refer to the [original model card](https://huggingface.co/TianheWu/VisualQuality-R1-7B) for more details on the model. | |
| ## Use with mlx | |
| ```bash | |
| pip install -U mlx-vlm | |
| ``` | |
| ```bash | |
| python -m mlx_vlm.generate --model mlx-community/VisualQuality-R1-7B-4bit --max-tokens 100 --temperature 0.0 --prompt "Describe this image." --image <path_to_image> | |
| ``` | |