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:
- 519955821e63ee82618b7eae861ce0c98b9e31d0fb52e965b37ff24a361da106
- Size of remote file:
- 12.9 MB
- SHA256:
- a1ba1edf6469264f1b3ac5e3fd54229457d8083d5872c055c088c45ba41a3f5e
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