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:
- 4fedd682447d484df9e1893ae0789bfb3a81ec7e6398643906f07c75067ee13c
- Size of remote file:
- 345 MB
- SHA256:
- f5c9c930c461fbf7e28d1e506ce8e4a08410e3a26c004e296e931b2cdc542c60
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