Instructions to use hf-internal-testing/tiny-random-TimesformerModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-TimesformerModel 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-TimesformerModel")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-TimesformerModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-TimesformerModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 87e4f6a54232b8942c45bad27a399aef27969459a9c2003089a9805b27326e5f
- Size of remote file:
- 260 kB
- SHA256:
- 12b080737485150bf69cb0749180cad6303efbb98fe340b711007778f151159d
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