Instructions to use mlx-community/NAFNet-REDS-width64 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/NAFNet-REDS-width64 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir NAFNet-REDS-width64 mlx-community/NAFNet-REDS-width64
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
File size: 603 Bytes
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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.
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