Instructions to use edadaltocg/resnet18_cifar100 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use edadaltocg/resnet18_cifar100 with timm:
import timm model = timm.create_model("hf_hub:edadaltocg/resnet18_cifar100", pretrained=True) - Notebooks
- Google Colab
- Kaggle
| { | |
| "architecture": "resnet18", | |
| "num_classes": 100, | |
| "num_features": 512, | |
| "pretrained_cfg": { | |
| "num_classes": 100, | |
| "input_size": [ | |
| 3, | |
| 32, | |
| 32 | |
| ], | |
| "pool_size": [ | |
| 4, | |
| 4 | |
| ], | |
| "crop_pct": 1, | |
| "interpolation": "bilinear", | |
| "fixed_input_size": false, | |
| "mean": [ | |
| 0.5071, | |
| 0.4867, | |
| 0.4408 | |
| ], | |
| "std": [ | |
| 0.2675, | |
| 0.2565, | |
| 0.2761 | |
| ], | |
| "first_conv": "conv1", | |
| "classifier": "fc" | |
| }, | |
| "url": "", | |
| "input_size": [ | |
| 3, | |
| 32, | |
| 32 | |
| ], | |
| "pool_size": [ | |
| 4, | |
| 4 | |
| ], | |
| "crop_pct": 1, | |
| "interpolation": "bilinear", | |
| "fixed_input_size": false, | |
| "mean": [ | |
| 0.5071, | |
| 0.4867, | |
| 0.4408 | |
| ], | |
| "std": [ | |
| 0.2675, | |
| 0.2565, | |
| 0.2761 | |
| ], | |
| "first_conv": "conv1", | |
| "classifier": "fc" | |
| } |