Instructions to use google/siglip2-large-patch16-384 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/siglip2-large-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-large-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-large-patch16-384", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Add architecture to config file
#3
by wirthual - opened
- config.json +3 -0
config.json
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{
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"initializer_factor": 1.0,
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"model_type": "siglip",
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"text_config": {
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{
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"architectures": [
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"SiglipModel"
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],
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"initializer_factor": 1.0,
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"model_type": "siglip",
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"text_config": {
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