Instructions to use hf-internal-testing/tiny-random-Swin2SRModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-Swin2SRModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="hf-internal-testing/tiny-random-Swin2SRModel")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-Swin2SRModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-Swin2SRModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6cf863d215dc8ab28733281c285a78a6f95b6350a1fcb9f3292a72b7c49db0f3
- Size of remote file:
- 156 kB
- SHA256:
- e7bdf974f3445859ef8541a7b80910cb03894982aad917ec1bd99f72420f1337
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