Instructions to use timm/vit_giantopt_patch16_siglip_gap_256.v2_webli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use timm/vit_giantopt_patch16_siglip_gap_256.v2_webli with timm:
import timm model = timm.create_model("hf-hub:timm/vit_giantopt_patch16_siglip_gap_256.v2_webli", pretrained=True) - Transformers
How to use timm/vit_giantopt_patch16_siglip_gap_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_giantopt_patch16_siglip_gap_256.v2_webli")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("timm/vit_giantopt_patch16_siglip_gap_256.v2_webli", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 135 Bytes
0687c74 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:b441265ff2e1dff14a710d2abb98eb68c4d24797895ae70dfd519102fdc5956b
size 4539536526
|