How to use hf-tiny-model-private/tiny-random-ChineseCLIPModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="hf-tiny-model-private/tiny-random-ChineseCLIPModel") 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("hf-tiny-model-private/tiny-random-ChineseCLIPModel") model = AutoModelForZeroShotImageClassification.from_pretrained("hf-tiny-model-private/tiny-random-ChineseCLIPModel", device_map="auto")
https://huggingface.co/hf-tiny-model-private/tiny-random-ChineseCLIPModel/resolve/a3b241a890730a6082c6fdf3f9c5129d05ec3650/special_tokens_map.json
hf download hf://hf-tiny-model-private/tiny-random-ChineseCLIPModel@a3b241a890730a6082c6fdf3f9c5129d05ec3650/special_tokens_map.json
curl -L -o special_tokens_map.json https://huggingface.co/hf-tiny-model-private/tiny-random-ChineseCLIPModel/resolve/a3b241a890730a6082c6fdf3f9c5129d05ec3650/special_tokens_map.json
