Instructions to use p1atdev/siglip2-base-patch16-384-vision with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use p1atdev/siglip2-base-patch16-384-vision with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="p1atdev/siglip2-base-patch16-384-vision")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("p1atdev/siglip2-base-patch16-384-vision") model = AutoModel.from_pretrained("p1atdev/siglip2-base-patch16-384-vision") - Notebooks
- Google Colab
- Kaggle
Only vision tower of google/siglip2-base-patch16-384.
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Base model
google/siglip2-base-patch16-384