Instructions to use hf-internal-testing/tiny-random-SwinModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-SwinModel 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-SwinModel")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-SwinModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-SwinModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1a9a89792df7d5d9b747b841dbc049338d40b0ccaae99965bf18e8cdd211ea1d
- Size of remote file:
- 368 kB
- SHA256:
- ccf33389d2e63243d7f948ca704b1aab607e8b726e4af1f31f61116961ad5e39
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