Instructions to use RISys-Lab/ReasonSigLIP2-go16-384-S0-Rea with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RISys-Lab/ReasonSigLIP2-go16-384-S0-Rea 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-S0-Rea") 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-S0-Rea") model = AutoModelForZeroShotImageClassification.from_pretrained("RISys-Lab/ReasonSigLIP2-go16-384-S0-Rea") - Notebooks
- Google Colab
- Kaggle
Commit History
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