Instructions to use dg845/univnet-dev with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dg845/univnet-dev with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="dg845/univnet-dev")# Load model directly from transformers import AutoFeatureExtractor, AutoModel extractor = AutoFeatureExtractor.from_pretrained("dg845/univnet-dev") model = AutoModel.from_pretrained("dg845/univnet-dev") - Notebooks
- Google Colab
- Kaggle
| { | |
| "architectures": [ | |
| "UnivNetModel" | |
| ], | |
| "initializer_range": 0.01, | |
| "kernel_predictor_conv_size": 3, | |
| "kernel_predictor_dropout": 0.0, | |
| "kernel_predictor_hidden_channels": 64, | |
| "kernel_predictor_num_blocks": 3, | |
| "leaky_relu_slope": 0.2, | |
| "model_hidden_channels": 32, | |
| "model_in_channels": 64, | |
| "model_type": "univnet", | |
| "num_mel_bins": 100, | |
| "resblock_dilation_sizes": [ | |
| [ | |
| 1, | |
| 3, | |
| 9, | |
| 27 | |
| ], | |
| [ | |
| 1, | |
| 3, | |
| 9, | |
| 27 | |
| ], | |
| [ | |
| 1, | |
| 3, | |
| 9, | |
| 27 | |
| ] | |
| ], | |
| "resblock_kernel_sizes": [ | |
| 3, | |
| 3, | |
| 3 | |
| ], | |
| "resblock_stride_sizes": [ | |
| 8, | |
| 8, | |
| 4 | |
| ], | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.35.0.dev0" | |
| } | |