Instructions to use arxyzan/data2vec-beit-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use arxyzan/data2vec-beit-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="arxyzan/data2vec-beit-base")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("arxyzan/data2vec-beit-base") model = AutoModel.from_pretrained("arxyzan/data2vec-beit-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b29217d2a620db976b7f8dd367c7176333ceede699cbcc6d46d4967d6c0c2d67
- Size of remote file:
- 343 MB
- SHA256:
- e1942d45a5003da3053504a1d9a7e12fcf70c0e90f2ee9a2b9c7553ba643acfd
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