Image Feature Extraction
timm
English
levljepa
vision-language
self-supervised-learning
feature-extraction
non-contrastive
jepa
vit
gpt2
Instructions to use lukaskuhndkfz/LeVLJEPA-ViT-B-DataComp-200k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use lukaskuhndkfz/LeVLJEPA-ViT-B-DataComp-200k with timm:
import timm model = timm.create_model("hf_hub:lukaskuhndkfz/LeVLJEPA-ViT-B-DataComp-200k", pretrained=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e7b4242b211ddfb1c5546535198110f7c3b4d13ba13559b51eaf8f8d90b4e514
- Size of remote file:
- 406 MB
- SHA256:
- 6203e88b77f29f9cdcd4f58561daab79892819bab4398abb8d9f100732f8121a
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