Instructions to use google/siglip-so400m-patch14-384 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/siglip-so400m-patch14-384 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="google/siglip-so400m-patch14-384") pipe( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png", candidate_labels=["animals", "humans", "landscape"], )# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForZeroShotImageClassification processor = AutoProcessor.from_pretrained("google/siglip-so400m-patch14-384") model = AutoModelForZeroShotImageClassification.from_pretrained("google/siglip-so400m-patch14-384", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from google/siglip-so400m-patch14-384: direct link, hf CLI and curl.
- Browser
- Download file 3.51 GB
-
https://huggingface.co/google/siglip-so400m-patch14-384/resolve/main/model.safetensors
- Command line
-
hf download hf://google/siglip-so400m-patch14-384/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/google/siglip-so400m-patch14-384/resolve/main/model.safetensors
3.51 GB
- Xet hash:
- f0bc04a32a6dbcac0e4f5659b2f97526603c59eb0f131904305edfe3c03a5a35
- Size of remote file:
- 3.51 GB
- SHA256:
- ea2abad2b7f8a9c1aa5e49a244d5d57ffa71c56f720c94bc5d240ef4d6e1d94a
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