Instructions to use audiohacking/pruna-vaed-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use audiohacking/pruna-vaed-mlx with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir pruna-vaed-mlx audiohacking/pruna-vaed-mlx
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
| { | |
| "variant": "pruna", | |
| "source": "PrunaAI/PrunaVAED", | |
| "latent_channels": 128, | |
| "out_channels": 3, | |
| "patch_size": 4, | |
| "patch_size_t": 1, | |
| "decoder_block_out_channels": [ | |
| 128, | |
| 256, | |
| 384, | |
| 1024 | |
| ], | |
| "decoder_layers_per_block": [ | |
| 4, | |
| 6, | |
| 4, | |
| 2, | |
| 2 | |
| ], | |
| "decoder_spatio_temporal_scaling": [ | |
| true, | |
| true, | |
| true, | |
| true | |
| ], | |
| "decoder_inject_noise": [ | |
| false, | |
| false, | |
| false, | |
| false, | |
| false | |
| ], | |
| "decoder_spatial_padding_mode": "zeros", | |
| "decoder_causal": false, | |
| "upsample_factor": [ | |
| 2, | |
| 2, | |
| 1, | |
| 2 | |
| ], | |
| "upsample_residual": [ | |
| false, | |
| false, | |
| false, | |
| false | |
| ], | |
| "upsample_type": [ | |
| "spatiotemporal", | |
| "spatiotemporal", | |
| "temporal", | |
| "spatial" | |
| ], | |
| "timestep_conditioning": false, | |
| "resnet_norm_eps": 1e-06, | |
| "scaling_factor": 1.0 | |
| } |