Instructions to use timm/vit_base_patch32_siglip_256.v2_webli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use timm/vit_base_patch32_siglip_256.v2_webli with timm:
import timm model = timm.create_model("hf_hub:timm/vit_base_patch32_siglip_256.v2_webli", pretrained=True) - Transformers
How to use timm/vit_base_patch32_siglip_256.v2_webli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="timm/vit_base_patch32_siglip_256.v2_webli")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("timm/vit_base_patch32_siglip_256.v2_webli", dtype="auto") - Notebooks
- Google Colab
- Kaggle
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