Instructions to use timm/vit_large_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_large_patch16_siglip_gap_384.v2_webli with timm:
import timm model = timm.create_model("hf_hub:timm/vit_large_patch16_siglip_gap_384.v2_webli", pretrained=True) - Transformers
How to use timm/vit_large_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_large_patch16_siglip_gap_384.v2_webli")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("timm/vit_large_patch16_siglip_gap_384.v2_webli", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6760e06fa6e2d283e1be3e432ab20d408ddaac61b5b1d7f4ad7a8ab5bca0d8cd
- Size of remote file:
- 1.21 GB
- SHA256:
- 35bde0871a48f5c51a6aa63c25fcdd4246d3de79e9ccea832051722382387f84
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