Instructions to use timm/vit_large_patch14_dinov2.lvd142m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use timm/vit_large_patch14_dinov2.lvd142m with timm:
import timm model = timm.create_model("hf-hub:timm/vit_large_patch14_dinov2.lvd142m", pretrained=True) - Transformers
How to use timm/vit_large_patch14_dinov2.lvd142m with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="timm/vit_large_patch14_dinov2.lvd142m")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("timm/vit_large_patch14_dinov2.lvd142m", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from timm/vit_large_patch14_dinov2.lvd142m: direct link, hf CLI and curl.
- Browser
- Download file 1.22 GB
-
https://huggingface.co/timm/vit_large_patch14_dinov2.lvd142m/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://timm/vit_large_patch14_dinov2.lvd142m/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/timm/vit_large_patch14_dinov2.lvd142m/resolve/main/pytorch_model.bin
1.22 GB
- Xet hash:
- 3eb6edc38b4f9542d7c51b31ba8a198966d31c3404b61c8ffde7932cc68ea0a1
- Size of remote file:
- 1.22 GB
- SHA256:
- 96413a203d0d00d673ae8de0a28959ae42f280106fa047b399fe9233fd31855c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.