Instructions to use RISys-Lab/ReasonSigLIP-So14-384-S2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RISys-Lab/ReasonSigLIP-So14-384-S2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="RISys-Lab/ReasonSigLIP-So14-384-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/ReasonSigLIP-So14-384-S2") model = AutoModelForZeroShotImageClassification.from_pretrained("RISys-Lab/ReasonSigLIP-So14-384-S2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8c62322ca4e59f6ab41660769e5b7402720cf2fe4363c89ed3cd5adfb0204374
- Size of remote file:
- 3.51 GB
- SHA256:
- 70ef4065a2acf92e350599452b141bcb870375928c900780ca81f8e915bb5f32
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