Instructions to use timm/vit_base_patch16_siglip_gap_256.webli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use timm/vit_base_patch16_siglip_gap_256.webli with timm:
import timm model = timm.create_model("hf_hub:timm/vit_base_patch16_siglip_gap_256.webli", pretrained=True) - Transformers
How to use timm/vit_base_patch16_siglip_gap_256.webli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="timm/vit_base_patch16_siglip_gap_256.webli")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("timm/vit_base_patch16_siglip_gap_256.webli", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 90e18ec15522095d7426ac7b667c3b17c62e0d262bc494d5f5f1bf7c86535311
- Size of remote file:
- 343 MB
- SHA256:
- 487f5f40f84f06e9cf439688b8dc6bb914131ed93d2a6d488772374cab5dfe2e
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