How to use RISys-Lab/ReasonCLIP-B32-S1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="RISys-Lab/ReasonCLIP-B32-S1") 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("RISys-Lab/ReasonCLIP-B32-S1") model = AutoModelForZeroShotImageClassification.from_pretrained("RISys-Lab/ReasonCLIP-B32-S1", device_map="auto")
https://huggingface.co/RISys-Lab/ReasonCLIP-B32-S1/resolve/refs%2Fpr%2F1/tokenizer.json
hf download hf://RISys-Lab/ReasonCLIP-B32-S1@refs/pr/1/tokenizer.json
curl -L -o tokenizer.json https://huggingface.co/RISys-Lab/ReasonCLIP-B32-S1/resolve/refs%2Fpr%2F1/tokenizer.json
