How to use rathi2023/owlvit-base-patch32 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-object-detection", model="rathi2023/owlvit-base-patch32")
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForZeroShotObjectDetection processor = AutoProcessor.from_pretrained("rathi2023/owlvit-base-patch32") model = AutoModelForZeroShotObjectDetection.from_pretrained("rathi2023/owlvit-base-patch32", device_map="auto")
https://huggingface.co/rathi2023/owlvit-base-patch32/resolve/main/vocab.json
hf download hf://rathi2023/owlvit-base-patch32/vocab.json
curl -L -o vocab.json https://huggingface.co/rathi2023/owlvit-base-patch32/resolve/main/vocab.json
