Instructions to use 1aurent/resnet34.tiatoolbox-pcam with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use 1aurent/resnet34.tiatoolbox-pcam with timm:
import timm model = timm.create_model("hf_hub:1aurent/resnet34.tiatoolbox-pcam", pretrained=True) - Notebooks
- Google Colab
- Kaggle
Download config.json from 1aurent/resnet34.tiatoolbox-pcam: direct link, hf CLI and curl.
- Browser
- Download file 740 Bytes
-
https://huggingface.co/1aurent/resnet34.tiatoolbox-pcam/resolve/main/config.json
- Command line
-
hf download hf://1aurent/resnet34.tiatoolbox-pcam/config.json
-
curl -L -o config.json https://huggingface.co/1aurent/resnet34.tiatoolbox-pcam/resolve/main/config.json
740 Bytes
| { | |
| "architecture": "resnet34", | |
| "num_classes": 2, | |
| "num_features": 512, | |
| "pretrained_cfg": { | |
| "tag": "tiatoolbox-pcam", | |
| "custom_load": false, | |
| "input_size": [ | |
| 3, | |
| 96, | |
| 96 | |
| ], | |
| "test_input_size": [ | |
| 3, | |
| 96, | |
| 96 | |
| ], | |
| "fixed_input_size": false, | |
| "interpolation": "bicubic", | |
| "crop_pct": 1.0, | |
| "test_crop_pct": 1.0, | |
| "crop_mode": "center", | |
| "mean": [ | |
| 0.0, | |
| 0.0, | |
| 0.0 | |
| ], | |
| "std": [ | |
| 1.0, | |
| 1.0, | |
| 1.0 | |
| ], | |
| "num_classes": 2, | |
| "pool_size": [ | |
| 7, | |
| 7 | |
| ], | |
| "first_conv": "conv1", | |
| "classifier": "fc", | |
| "origin_url": "https://github.com/huggingface/pytorch-image-models", | |
| "paper_ids": "arXiv:2110.00476" | |
| } | |
| } |