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:
- 8238c78cb0b3f6f58e869e73f38eac0002e7e9e0d1a5b6aed329c0eca5bfc1bc
- Size of remote file:
- 156 kB
- SHA256:
- 7c21b1656c0982ceb9ff524b2d658ca5776c0d5fb6426f96820166be1c8ee796
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