Instructions to use fal/AuraSR-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fal/AuraSR-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-to-image", model="fal/AuraSR-v2")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("fal/AuraSR-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ff1cd598e4470274e1912bf39022f25dcfa63d85dee40c63880202401542a5e6
- Size of remote file:
- 2.47 GB
- SHA256:
- 8028efd10725528bd81b5906f25dea3210bfe178ac5130a3f1cab3fd720d8b7a
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