Instructions to use openai/clip-vit-large-patch14-336 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openai/clip-vit-large-patch14-336 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="openai/clip-vit-large-patch14-336") pipe( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png", candidate_labels=["animals", "humans", "landscape"], )# Load model directly from transformers import AutoProcessor, AutoModelForZeroShotImageClassification processor = AutoProcessor.from_pretrained("openai/clip-vit-large-patch14-336") model = AutoModelForZeroShotImageClassification.from_pretrained("openai/clip-vit-large-patch14-336") - Notebooks
- Google Colab
- Kaggle
Adding ONNX file of this model
#16
by motirodan - opened
- onnx/image_model.onnx +3 -0
- onnx/text_model.onnx +3 -0
onnx/image_model.onnx
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version https://git-lfs.github.com/spec/v1
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oid sha256:10f7db401e8cebb04fb9bb0cb1671dde3a7eb76cc54ca1757aa7b3d4fdaba5dc
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size 1217624152
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onnx/text_model.onnx
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version https://git-lfs.github.com/spec/v1
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oid sha256:a2f3cc2724d85f29bdb8126e93494c582d9a14649ed867ae3b680f602a9224b3
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size 494827353
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