Instructions to use openai/clip-vit-base-patch32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openai/clip-vit-base-patch32 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="openai/clip-vit-base-patch32") 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("openai/clip-vit-base-patch32") model = AutoModelForZeroShotImageClassification.from_pretrained("openai/clip-vit-base-patch32", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Fix a small formatting bug
Verified signatureThe code example used "python3" in the markdown as the language, but this prevents it from showing up with syntax highlighting. I've just changed it to "python" which fixes the error.51fe76c
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Updates incorrect tokenizer configuration file (#13)
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