Instructions to use RISys-Lab/ReasonSigLIP2-So14-384-S1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RISys-Lab/ReasonSigLIP2-So14-384-S1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="RISys-Lab/ReasonSigLIP2-So14-384-S1") 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-So14-384-S1") model = AutoModelForZeroShotImageClassification.from_pretrained("RISys-Lab/ReasonSigLIP2-So14-384-S1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 86e1efd46a02a10d400f717311bb50a6bdaa3eaeead8a1e49754f75330c96191
- Size of remote file:
- 2.27 GB
- SHA256:
- fad424241e511dc60e6935b2a3bd90ab200427b946bd7f47a498110a5030b3c1
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