Instructions to use dangkhoadl/AudioResNet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dangkhoadl/AudioResNet with Transformers:
# Load model directly from transformers import AutoImageProcessor, ResNetForAudioClassification processor = AutoImageProcessor.from_pretrained("dangkhoadl/AudioResNet") model = ResNetForAudioClassification.from_pretrained("dangkhoadl/AudioResNet") - Notebooks
- Google Colab
- Kaggle
| { | |
| "architectures": [ | |
| "ResNetForAudioClassification" | |
| ], | |
| "id2label": { | |
| "0": "LABEL_0", | |
| "1": "LABEL_1", | |
| "2": "LABEL_2", | |
| "3": "LABEL_3" | |
| }, | |
| "label2id": { | |
| "LABEL_0": 0, | |
| "LABEL_1": 1, | |
| "LABEL_2": 2, | |
| "LABEL_3": 3 | |
| }, | |
| "model_type": "resnet", | |
| "resnet_arch": "resnet_152", | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.30.2" | |
| } | |