Instructions to use google/siglip-base-patch16-224 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/siglip-base-patch16-224 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="google/siglip-base-patch16-224") pipe( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png", candidate_labels=["animals", "humans", "landscape"], )# Load model directly from transformers import AutoProcessor, AutoModelForZeroShotImageClassification processor = AutoProcessor.from_pretrained("google/siglip-base-patch16-224") model = AutoModelForZeroShotImageClassification.from_pretrained("google/siglip-base-patch16-224") - Notebooks
- Google Colab
- Kaggle
Upload tokenizer.json for fast tokenizer support
#4
by itazap HF Staff - opened
giffmana changed pull request status to merged