Instructions to use Superlore/clip-vit-large-patch14 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Superlore/clip-vit-large-patch14 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="Superlore/clip-vit-large-patch14") pipe( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png", candidate_labels=["animals", "humans", "landscape"], )# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForZeroShotImageClassification processor = AutoProcessor.from_pretrained("Superlore/clip-vit-large-patch14") model = AutoModelForZeroShotImageClassification.from_pretrained("Superlore/clip-vit-large-patch14", 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.cb4b71f
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nits throw on bad request
0xnewton-superlore426785e -
refactor inference request structure
0xnewton-superlored318463 -
change owner to superlore user account
0xnewton-superlore7a7f986 -
adds handler.py for custom inference
0xnewton-superlored26a895
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initial commit - copy https://huggingface.co/openai/clip-vit-large-patch14
0xnewton-superlore93cf9b4