How to use Balajim57/zero-shot-vitb32 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="Balajim57/zero-shot-vitb32") 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("Balajim57/zero-shot-vitb32") model = AutoModelForZeroShotImageClassification.from_pretrained("Balajim57/zero-shot-vitb32", device_map="auto")
https://huggingface.co/Balajim57/zero-shot-vitb32/resolve/main/tokenizer.json
hf download hf://Balajim57/zero-shot-vitb32/tokenizer.json
curl -L -o tokenizer.json https://huggingface.co/Balajim57/zero-shot-vitb32/resolve/main/tokenizer.json
