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:
- 8ce5c5d06ceec42be538cc867f229b5192e8f01f60d3405098bf6f013ddca21c
- Size of remote file:
- 26.5 MB
- SHA256:
- 175d18061df5670fb1545e023c86df9a8a0568ee770c3105d713884dc0f41c3b
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