Instructions to use google/siglip2-giant-opt-patch16-256 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/siglip2-giant-opt-patch16-256 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="google/siglip2-giant-opt-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 AutoModel model = AutoModel.from_pretrained("google/siglip2-giant-opt-patch16-256", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Upload README.md with huggingface_hub
Verified signature46d7129 -
Upload README.md with huggingface_hub (#1)
Verified signature- Upload README.md with huggingface_hub (bbb7c42c657e56693fb0f3a457052523a6dc9867)05d645a
-
Upload config
Verified signaturee399f0c
-
Upload processor
Verified signaturecf84862 -
Upload model
Verified signatured2335d0 -
initial commit
Verified signature20992cd