Instructions to use Veritone/siglip2-base-patch16-224 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Veritone/siglip2-base-patch16-224 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="Veritone/siglip2-base-patch16-224") 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("Veritone/siglip2-base-patch16-224") model = AutoModelForZeroShotImageClassification.from_pretrained("Veritone/siglip2-base-patch16-224", device_map="auto") - Notebooks
- Google Colab
- Kaggle
fix-vision-tower
#1
by dietmar-veri - opened
- config.json +3 -8
- model.safetensors +2 -2
- text_model.safetensors +3 -0
config.json
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"model_type": "siglip",
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"text_config": {
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"model_type": "siglip_text_model",
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"vocab_size": 256000
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"pad_token_id": 0
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},
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"transformers_version": "4.49.0.dev0",
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"vision_config": {
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"model_type": "siglip_vision_model"
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}
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"SiglipModel"
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],
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"max_position_embeddings": 64
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}
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"model_type": "siglip",
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"text_config": {
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"model_type": "siglip_text_model",
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"vocab_size": 256000
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},
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"transformers_version": "4.49.0.dev0",
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"vision_config": {
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"model_type": "siglip_vision_model"
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}
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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oid sha256:325421d6b19e023ba08c05cd3cbd8670c0d1666f2dafe81d1ef2893bff350784
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size 1129238664
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text_model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:325421d6b19e023ba08c05cd3cbd8670c0d1666f2dafe81d1ef2893bff350784
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size 1129238664
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