Instructions to use timm/vit_large_patch16_siglip_512.v2_webli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use timm/vit_large_patch16_siglip_512.v2_webli with timm:
import timm model = timm.create_model("hf_hub:timm/vit_large_patch16_siglip_512.v2_webli", pretrained=True) - Transformers
How to use timm/vit_large_patch16_siglip_512.v2_webli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="timm/vit_large_patch16_siglip_512.v2_webli")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("timm/vit_large_patch16_siglip_512.v2_webli", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 491b2ca49f57b6569c64b433c6bda0aaccb01033c2cd1428a3917a9f38c7fdeb
- Size of remote file:
- 1.27 GB
- SHA256:
- 04dca661cd82a8b44e390b680434292aaa8eaa44be2fbca308ba28c27fef8b13
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