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:
- c9912ce06da0442111bc46a1e324f2825a30bdb20636de1c1fc9806c21c74b37
- Size of remote file:
- 3.96 kB
- SHA256:
- 9244e800ffbd92379b525015bb89f779c9e73ecd34803b91542ba481428432c9
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