| # Pretrained models | |
| The models will be downloaded automatically when you run the demo script. MD5 checksums are provided in `mmaudio/utils/download_utils.py`. | |
| The models are also available at https://huggingface.co/hkchengrex/MMAudio/tree/main | |
| | Model | Download link | File size | | |
| | -------- | ------- | ------- | | |
| | Flow prediction network, small 16kHz | <a href="https://huggingface.co/hkchengrex/MMAudio/resolve/main/weights/mmaudio_small_16k.pth" download="mmaudio_small_16k.pth">mmaudio_small_16k.pth</a> | 601M | | |
| | Flow prediction network, small 44.1kHz | <a href="https://huggingface.co/hkchengrex/MMAudio/resolve/main/weights/mmaudio_small_44k.pth" download="mmaudio_small_44k.pth">mmaudio_small_44k.pth</a> | 601M | | |
| | Flow prediction network, medium 44.1kHz | <a href="https://huggingface.co/hkchengrex/MMAudio/resolve/main/weights/mmaudio_medium_44k.pth" download="mmaudio_medium_44k.pth">mmaudio_medium_44k.pth</a> | 2.4G | | |
| | Flow prediction network, large 44.1kHz | <a href="https://huggingface.co/hkchengrex/MMAudio/resolve/main/weights/mmaudio_large_44k.pth" download="mmaudio_large_44k.pth">mmaudio_large_44k.pth</a> | 3.9G | | |
| | Flow prediction network, large 44.1kHz, v2 **(recommended)** | <a href="https://huggingface.co/hkchengrex/MMAudio/resolve/main/weights/mmaudio_large_44k_v2.pth" download="mmaudio_large_44k_v2.pth">mmaudio_large_44k_v2.pth</a> | 3.9G | | |
| | 16kHz VAE | <a href="https://github.com/hkchengrex/MMAudio/releases/download/v0.1/v1-16.pth">v1-16.pth</a> | 655M | | |
| | 16kHz BigVGAN vocoder (from Make-An-Audio 2) |<a href="https://github.com/hkchengrex/MMAudio/releases/download/v0.1/best_netG.pt">best_netG.pt</a> | 429M | | |
| | 44.1kHz VAE |<a href="https://github.com/hkchengrex/MMAudio/releases/download/v0.1/v1-44.pth">v1-44.pth</a> | 1.2G | | |
| | Synchformer visual encoder |<a href="https://github.com/hkchengrex/MMAudio/releases/download/v0.1/synchformer_state_dict.pth">synchformer_state_dict.pth</a> | 907M | | |
| To run the model, you need four components: a flow prediction network, visual feature extractors (Synchformer and CLIP, CLIP will be downloaded automatically), a VAE, and a vocoder. VAEs and vocoders are specific to the sampling rate (16kHz or 44.1kHz) and not model sizes. | |
| The 44.1kHz vocoder will be downloaded automatically. | |
| The `_v2` model performs worse in benchmarking (e.g., in Fréchet distance), but, in my experience, generalizes better to new data. | |
| The expected directory structure (full): | |
| ```bash | |
| MMAudio | |
| ├── ext_weights | |
| │ ├── best_netG.pt | |
| │ ├── synchformer_state_dict.pth | |
| │ ├── v1-16.pth | |
| │ └── v1-44.pth | |
| ├── weights | |
| │ ├── mmaudio_small_16k.pth | |
| │ ├── mmaudio_small_44k.pth | |
| │ ├── mmaudio_medium_44k.pth | |
| │ ├── mmaudio_large_44k.pth | |
| │ └── mmaudio_large_44k_v2.pth | |
| └── ... | |
| ``` | |
| The expected directory structure (minimal, for the recommended model only): | |
| ```bash | |
| MMAudio | |
| ├── ext_weights | |
| │ ├── synchformer_state_dict.pth | |
| │ └── v1-44.pth | |
| ├── weights | |
| │ └── mmaudio_large_44k_v2.pth | |
| └── ... | |
| ``` | |