Instructions to use maurice-fp/SACBenchmark-train.vgg13.CIFAR10.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use maurice-fp/SACBenchmark-train.vgg13.CIFAR10.0 with timm:
import timm model = timm.create_model("hf_hub:maurice-fp/SACBenchmark-train.vgg13.CIFAR10.0", pretrained=True) - Notebooks
- Google Colab
- Kaggle
| { | |
| "architecture": "vgg13", | |
| "num_classes": 10, | |
| "num_features": 4096, | |
| "pretrained_cfg": { | |
| "crop_mode": "center", | |
| "first_conv": "features[0]", | |
| "classifier": "classifier[6]", | |
| "input_size": [ | |
| 3, | |
| 32, | |
| 32 | |
| ], | |
| "num_classes": 10, | |
| "num_features": 4096, | |
| "mean": [ | |
| 0.4914, | |
| 0.4822, | |
| 0.4465 | |
| ], | |
| "std": [ | |
| 0.2023, | |
| 0.1994, | |
| 0.201 | |
| ] | |
| } | |
| } |