Instructions to use google/siglip-base-patch16-256 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/siglip-base-patch16-256 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="google/siglip-base-patch16-256") 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("google/siglip-base-patch16-256") model = AutoModelForZeroShotImageClassification.from_pretrained("google/siglip-base-patch16-256", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Upload tokenizer.json
Verified signaturebe74895
-
Update README.md
Verified signature6abf7a2 -
Update README.md
Verified signatured856bf1
-
Update README.md
eb3becd -
Update README.md
d307e38 -
Update README.md
5526730 -
Update README.md
fddc1bd -
Update README.md
caf4dcd -
Update README.md
a58a179 -
Update README.md
6cffdc6 -
Create README.md
415aa2d -
Upload processor
c5a4d02 -
Upload model
63c4247 -
initial commit
87d593c