Instructions to use mlx-community/EfRLFN-x2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/EfRLFN-x2 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir EfRLFN-x2 mlx-community/EfRLFN-x2
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
File size: 600 Bytes
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license: mit
library_name: mlx
pipeline_tag: image-to-image
tags: [mlx, super-resolution, efrlfn]
base_model: EvgeneyBogatyrev/EfRLFN
---
# EfRLFN x2 (MLX)
Apple MLX port of [EfRLFN](https://github.com/EvgeneyBogatyrev/EfRLFN) (ICLR 2026), x2 super-resolution.
PT-vs-MLX parity ~1e-6. Realtime on Apple Silicon (270x480 -> 1080x1920 ~0.06s for x4).
```python
from efrlfn_mlx import EfRLFNConfig
from efrlfn_mlx.pipeline import load_model, upscale_to_file
m = load_model("model.safetensors", EfRLFNConfig.x2())
upscale_to_file(m, "lr.png", "sr.png")
```
MIT, derived from EvgeneyBogatyrev/EfRLFN.
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