Instructions to use RobotIX-Lab/siglip2-base-patch16-224 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RobotIX-Lab/siglip2-base-patch16-224 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="RobotIX-Lab/siglip2-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 AutoModel model = AutoModel.from_pretrained("RobotIX-Lab/siglip2-base-patch16-224", dtype="auto") - Notebooks
- Google Colab
- Kaggle
File size: 133 Bytes
541d77f | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:cb9140fae3ac5122c972d37adf83e1248471a38147ad76f8215c8872c6fd8322
size 34363039
|