Instructions to use timm/vit_base_patch16_siglip_gap_384.v2_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_384.v2_webli with timm:
import timm model = timm.create_model("hf_hub:timm/vit_base_patch16_siglip_gap_384.v2_webli", pretrained=True) - Transformers
How to use timm/vit_base_patch16_siglip_gap_384.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_patch16_siglip_gap_384.v2_webli")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("timm/vit_base_patch16_siglip_gap_384.v2_webli", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ce48014e185fee81dc542972b921c132f5f5d95eba6af95844d32620c9eca90c
- Size of remote file:
- 344 MB
- SHA256:
- 0120e2f82b9683319ea458fc772a093b750a364ec7cd634a09fe82dd0b31232a
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