Instructions to use Adf/siglip2_finetune with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Adf/siglip2_finetune with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="Adf/siglip2_finetune") 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("Adf/siglip2_finetune") model = AutoModelForZeroShotImageClassification.from_pretrained("Adf/siglip2_finetune") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1210c552831a07ec8c6011b1ba5b184d477d9eafdb785ebedfd724ed9faf2243
- Size of remote file:
- 34.4 MB
- SHA256:
- 5b6335655383213b50aa2469afaefecd3e17a342c85b57b7af52b5e270a4b745
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