Instructions to use hf-internal-testing/tiny-random-VideoMAEModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-VideoMAEModel 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-VideoMAEModel")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-VideoMAEModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-VideoMAEModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8414ed9ef458661116f14fb8722c4aab27d62d78e4b5cd4cac08cdc6dc909589
- Size of remote file:
- 163 kB
- SHA256:
- a726647eed9f19ad327a448f0c39bb409110e9487702d4f929aa4122968a8b4a
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