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")
https://huggingface.co/openai/clip-vit-base-patch32/resolve/3d74acf9a28c67741b2f4f2ea7635f0aaf6f0268/tokenizer.json
hf download hf://openai/clip-vit-base-patch32@3d74acf9a28c67741b2f4f2ea7635f0aaf6f0268/tokenizer.json
curl -L -o tokenizer.json https://huggingface.co/openai/clip-vit-base-patch32/resolve/3d74acf9a28c67741b2f4f2ea7635f0aaf6f0268/tokenizer.json
