Instructions to use hf-tiny-model-private/tiny-random-VideoMAEModel 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-VideoMAEModel 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-VideoMAEModel")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-tiny-model-private/tiny-random-VideoMAEModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-VideoMAEModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a7131503d217fcf03f752840dd029b02b4e3e91e811a0ac0621a4feb6a3d154b
- Size of remote file:
- 146 kB
- SHA256:
- cf153e056bdb59086ca8f5a50ba900726c9d0296b95658f932b9da6e5a2bb726
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