Instructions to use hf-tiny-model-private/tiny-random-Swin2SRModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-Swin2SRModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="hf-tiny-model-private/tiny-random-Swin2SRModel")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-tiny-model-private/tiny-random-Swin2SRModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-Swin2SRModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dcb55ad2ba1517e04d7b044738b680704cc2af72b46ab34d99c4c8841616f1f4
- Size of remote file:
- 135 kB
- SHA256:
- eee1ff568dfba459c136072fedd14da56ad8d99b30a8dde183067ffdadacce0c
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