Instructions to use hf-internal-testing/tiny-random-VideoMAEForVideoClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-VideoMAEForVideoClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("video-classification", model="hf-internal-testing/tiny-random-VideoMAEForVideoClassification")# Load model directly from transformers import AutoImageProcessor, AutoModelForVideoClassification processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-VideoMAEForVideoClassification") model = AutoModelForVideoClassification.from_pretrained("hf-internal-testing/tiny-random-VideoMAEForVideoClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f31aed195177c7b30c7576fc12e2048c8e80ba29e47f0d13df8bb7b8f169c818
- Size of remote file:
- 148 kB
- SHA256:
- 61a6287a25b8e0cdf8b2728047e6d160c6a44bb9dd5fc11b12b48f3192cdd4ef
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