Instructions to use mlx-community/NAFNet-GoPro-width64 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/NAFNet-GoPro-width64 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir NAFNet-GoPro-width64 mlx-community/NAFNet-GoPro-width64
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
| nafnet-mlx | |
| Apple MLX port of NAFNet (Simple Baselines for Image Restoration). | |
| This work is licensed under the MIT License. | |
| Derived from: | |
| - megvii-research/NAFNet (MIT) — official PyTorch implementation and pretrained weights. | |
| Chen et al., "Simple Baselines for Image Restoration", ECCV 2022 (arXiv:2204.04676). | |
| TLC (test-time local converter) from Chu et al., arXiv:2112.04491. | |
| - Built on the BasicSR framework conventions (Apache-2.0). | |
| Pretrained weights (REDS / SIDD / GoPro width64) are the official megvii-research releases, | |
| converted to MLX safetensors. Original weights are MIT-licensed. | |