Instructions to use Mooshie/eva02_large_patch14_448.dbv4-full with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use Mooshie/eva02_large_patch14_448.dbv4-full with timm:
import timm model = timm.create_model("hf_hub:Mooshie/eva02_large_patch14_448.dbv4-full", pretrained=True) - Transformers
How to use Mooshie/eva02_large_patch14_448.dbv4-full with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Mooshie/eva02_large_patch14_448.dbv4-full") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Mooshie/eva02_large_patch14_448.dbv4-full", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dfdb25292c8b24c23b5f7510344a76255ba6a9f2a7b0cd0f6708da749c051757
- Size of remote file:
- 1.27 GB
- SHA256:
- db1ea999ba4bbaadf4884579c6390947f4b7856d62df965344fe3d6a4edeca1d
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