Instructions to use LinStevenn/videomae-base-readminds-assignment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LinStevenn/videomae-base-readminds-assignment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("video-classification", model="LinStevenn/videomae-base-readminds-assignment")# Load model directly from transformers import AutoImageProcessor, AutoModelForVideoClassification processor = AutoImageProcessor.from_pretrained("LinStevenn/videomae-base-readminds-assignment") model = AutoModelForVideoClassification.from_pretrained("LinStevenn/videomae-base-readminds-assignment", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- de930bd0d02c7ad0a1d019a3df6f5f7cfa7c4069e8877a900e4cc3f0f5d3df1f
- Size of remote file:
- 5.3 kB
- SHA256:
- 7b8cc91c002fd7c51c3bf44862c85f07db6c2e675134f8faa29c42f62e10ca39
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