Instructions to use scizzum/model_10_22_run with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use scizzum/model_10_22_run with timm:
import timm model = timm.create_model("hf_hub:scizzum/model_10_22_run", pretrained=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e264f1b2c36013671716a72f1eca55ddef50fdc9c223abb233785be5c0d7d9a7
- Size of remote file:
- 4.04 GB
- SHA256:
- 0fb67ad2d6c3780e57d990939dbe9b398fe1669540aea053461dde4c79483972
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.