Instructions to use facebook/vit-msn-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/vit-msn-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="facebook/vit-msn-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("facebook/vit-msn-base") model = AutoModel.from_pretrained("facebook/vit-msn-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Adding `safetensors` variant of this model
Verified signatureThis is an automated PR created with https://huggingface.co/spaces/safetensors/convert This new file is equivalent to `pytorch_model.bin` but safe in the sense that no arbitrary code can be put into it. These files also happen to load much faster than their pytorch counterpart: https://colab.research.google.com/github/huggingface/notebooks/blob/main/safetensors_doc/en/speed.ipynb The widgets on your model page will run using this model even if this is not merged making sure the file actually works. If you find any issues: please report here: https://huggingface.co/spaces/safetensors/convert/discussions Feel free to ignore this PR.5beb14f
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Update config.json (#2)
- Update config.json (ec62a5e5391847144177bf8089a2049e1e255a82) Co-authored-by: Sayak Paul <sayakpaul@users.noreply.huggingface.co>8c72143
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Create README.md (#1)
- Create README.md (99787d09c374910b6530a6499413d24890975e51) Co-authored-by: Sayak Paul <sayakpaul@users.noreply.huggingface.co>a41f3ed
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