Instructions to use team-lucid/siglip-base-patch32-ko with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use team-lucid/siglip-base-patch32-ko with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="team-lucid/siglip-base-patch32-ko") 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("team-lucid/siglip-base-patch32-ko") model = AutoModelForZeroShotImageClassification.from_pretrained("team-lucid/siglip-base-patch32-ko", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from team-lucid/siglip-base-patch32-ko: direct link, hf CLI and curl.
- Browser
- Download file 569 MB
-
https://huggingface.co/team-lucid/siglip-base-patch32-ko/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://team-lucid/siglip-base-patch32-ko/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/team-lucid/siglip-base-patch32-ko/resolve/main/flax_model.msgpack
569 MB
- Xet hash:
- 286c18f82870890cbe16d0738024a94b8a545c04f482ca9eec53c7929e56cde0
- Size of remote file:
- 569 MB
- SHA256:
- d663035c01204ed77bd79e021e9ba09128e85168032b34dacaa0ed2601d00bd4
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