Instructions to use bytedance-research/UNO with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bytedance-research/UNO with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-to-image", model="bytedance-research/UNO")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("bytedance-research/UNO", dtype="auto") - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- 4243269d9a230e22c2d1e5f088105b8225c613425d61cd8c88160aa2543d059d
- Size of remote file:
- 622 kB
- SHA256:
- 05e4ab1c204a10cb08c9f4f4c332f824b332e3fadec5a7ccc99f0fa1a93c0739
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