Instructions to use toolevalxm/MedVisionNet-ChestXray with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use toolevalxm/MedVisionNet-ChestXray with timm:
import timm model = timm.create_model("hf-hub:toolevalxm/MedVisionNet-ChestXray", pretrained=True) - Notebooks
- Google Colab
- Kaggle
Download config.json from toolevalxm/MedVisionNet-ChestXray: direct link, hf CLI and curl.
- Browser
- Download file 130 Bytes
-
https://huggingface.co/toolevalxm/MedVisionNet-ChestXray/resolve/main/config.json
- Command line
-
hf download hf://toolevalxm/MedVisionNet-ChestXray/config.json
-
curl -L -o config.json https://huggingface.co/toolevalxm/MedVisionNet-ChestXray/resolve/main/config.json
130 Bytes
| { | |
| "model_type": "resnet", | |
| "architectures": ["ResNetForImageClassification"], | |
| "num_labels": 14, | |
| "image_size": 512 | |
| } |