Instructions to use sgugger/resnet50d with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use sgugger/resnet50d with timm:
import timm model = timm.create_model("hf_hub:sgugger/resnet50d", pretrained=True) - Notebooks
- Google Colab
- Kaggle
| { | |
| "architecture": "resnet50d", | |
| "classifier": "fc", | |
| "crop_pct": 0.875, | |
| "first_conv": "conv1.0", | |
| "input_size": [ | |
| 3, | |
| 224, | |
| 224 | |
| ], | |
| "interpolation": "bicubic", | |
| "mean": [ | |
| 0.485, | |
| 0.456, | |
| 0.406 | |
| ], | |
| "num_classes": 1000, | |
| "pool_size": [ | |
| 7, | |
| 7 | |
| ], | |
| "std": [ | |
| 0.229, | |
| 0.224, | |
| 0.225 | |
| ] | |
| } | |