Instructions to use hf-tiny-model-private/tiny-random-VideoMAEForVideoClassification 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-VideoMAEForVideoClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("video-classification", model="hf-tiny-model-private/tiny-random-VideoMAEForVideoClassification")# Load model directly from transformers import AutoImageProcessor, AutoModelForVideoClassification processor = AutoImageProcessor.from_pretrained("hf-tiny-model-private/tiny-random-VideoMAEForVideoClassification") model = AutoModelForVideoClassification.from_pretrained("hf-tiny-model-private/tiny-random-VideoMAEForVideoClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dbdef4720fc593b698ee93387f73cc1a94f34d7a2383c7704a67527f01416308
- Size of remote file:
- 148 kB
- SHA256:
- 6419fe28e00963250ec2402cc76df26b894e90a2a21309d28f47b2ea188efe98
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