Instructions to use AnhLedger/Videomae_SignLanguage with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnhLedger/Videomae_SignLanguage with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("video-classification", model="AnhLedger/Videomae_SignLanguage")# Load model directly from transformers import AutoImageProcessor, AutoModelForVideoClassification processor = AutoImageProcessor.from_pretrained("AnhLedger/Videomae_SignLanguage") model = AutoModelForVideoClassification.from_pretrained("AnhLedger/Videomae_SignLanguage", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 64af35e7ba97a3cb0d20ab68fc1e15bf6eabf4ddf22e9b6bd6b06db168ceee94
- Size of remote file:
- 345 MB
- SHA256:
- 307fc23574a7749a50bf76a74cc141fa80040dcba20c26d41c5ef73ae16cc1aa
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