Instructions to use MiVaCod/xray-image-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- fastai
How to use MiVaCod/xray-image-classification with fastai:
from huggingface_hub import from_pretrained_fastai learn = from_pretrained_fastai("MiVaCod/xray-image-classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 96f0dcf7f838829aa151a2822b9215a994fd727569dfc3571c344cddd1f2d01d
- Size of remote file:
- 47 MB
- SHA256:
- dce135019ef85708ac134626de0c653ca04f72861e543769d6b70ca749d76f79
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.