Instructions to use RISys-Lab/ReasonSigLIP-So14-384-S1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RISys-Lab/ReasonSigLIP-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/ReasonSigLIP-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/ReasonSigLIP-So14-384-S1") model = AutoModelForZeroShotImageClassification.from_pretrained("RISys-Lab/ReasonSigLIP-So14-384-S1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ed2d509a393d44da94decfba376c5d42b2293c7f2bde07b35b5e769384ffc83c
- Size of remote file:
- 1.76 GB
- SHA256:
- 80afeff3d58bf7bab40fba54ebc005708c3cf236d40912c2a1f4096fd1ec5ea9
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