Instructions to use RISys-Lab/ReasonSigLIP2-go16-384-S2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RISys-Lab/ReasonSigLIP2-go16-384-S2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="RISys-Lab/ReasonSigLIP2-go16-384-S2") 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("RISys-Lab/ReasonSigLIP2-go16-384-S2") model = AutoModelForZeroShotImageClassification.from_pretrained("RISys-Lab/ReasonSigLIP2-go16-384-S2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1cc2031661080cf926791605d802fb2fdeee15e0fffb5d76c860749ca16b678f
- Size of remote file:
- 34.4 MB
- SHA256:
- cb9140fae3ac5122c972d37adf83e1248471a38147ad76f8215c8872c6fd8322
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