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
File size: 133 Bytes
ab7beb8 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:cb9140fae3ac5122c972d37adf83e1248471a38147ad76f8215c8872c6fd8322
size 34363039
|