Instructions to use google/siglip2-base-patch16-384 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/siglip2-base-patch16-384 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="google/siglip2-base-patch16-384") pipe( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png", candidate_labels=["animals", "humans", "landscape"], )# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("google/siglip2-base-patch16-384", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 276 Bytes
88d6106 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 | {
"initializer_factor": 1.0,
"model_type": "siglip",
"text_config": {
"model_type": "siglip_text_model",
"vocab_size": 256000
},
"transformers_version": "4.49.0.dev0",
"vision_config": {
"image_size": 384,
"model_type": "siglip_vision_model"
}
}
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