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:
- 27844a6987af0c62bd7e285618cccb8a442efa73309e31d492ce9afd1b5f1dfc
- Size of remote file:
- 165 kB
- SHA256:
- 6673e9d8ac037dcf46e8e591d48c3da0e3a99ba6fb5525df96a214d4dc543f8c
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