Instructions to use Shawon16/VideoMAE_Base_3_class_codeCheck with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Shawon16/VideoMAE_Base_3_class_codeCheck with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("video-classification", model="Shawon16/VideoMAE_Base_3_class_codeCheck")# Load model directly from transformers import AutoImageProcessor, AutoModelForVideoClassification processor = AutoImageProcessor.from_pretrained("Shawon16/VideoMAE_Base_3_class_codeCheck") model = AutoModelForVideoClassification.from_pretrained("Shawon16/VideoMAE_Base_3_class_codeCheck", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 277fb7a3ade355bf61be97431d2b30ee4c9089269b9b797e87a2941fbe89fc8c
- Size of remote file:
- 12.8 MB
- SHA256:
- 3a14a261ff4f87a79277cf37bcf8da963e73044da82f470bc43d4e19555ef51f
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