Instructions to use nliampi/custom-resnet50d with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nliampi/custom-resnet50d with Transformers:
# Load model directly from transformers import AutoImageProcessor, ResnetModelForImageClassification processor = AutoImageProcessor.from_pretrained("nliampi/custom-resnet50d") model = ResnetModelForImageClassification.from_pretrained("nliampi/custom-resnet50d") - Notebooks
- Google Colab
- Kaggle
| { | |
| "architectures": [ | |
| "ResnetModelForImageClassification" | |
| ], | |
| "avg_down": true, | |
| "base_width": 64, | |
| "block_type": "bottleneck", | |
| "cardinality": 1, | |
| "dtype": "float32", | |
| "input_channels": 3, | |
| "layers": [ | |
| 3, | |
| 4, | |
| 6, | |
| 3 | |
| ], | |
| "model_type": "resnet", | |
| "num_classes": 1000, | |
| "stem_type": "deep", | |
| "stem_width": 32, | |
| "transformers_version": "4.56.1" | |
| } | |