Instructions to use aneforge/clip-vit-base-patch32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ANEForge
How to use aneforge/clip-vit-base-patch32 with ANEForge:
# Run this model on the Apple Neural Engine, without CoreML. import aneforge as af clip = af.load_clip("aneforge/clip-vit-base-patch32") labels = clip.classify(image, ["a photo of a cat", "a photo of a dog"]) # image: a PIL.Image; zero-shot (label, prob) - 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.15fcb26 -
drop tf_model.h5: ANEForge loads safetensors
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duplicate openai/clip-vit-base-patch32 weights, tagged for ANEForge
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initial commit
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