Instructions to use Jahmori-R/resepformer-librimix2spk with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- speechbrain
How to use Jahmori-R/resepformer-librimix2spk with speechbrain:
# interface not specified in config.json
- Notebooks
- Google Colab
- Kaggle
Download hyperparams.yaml from Jahmori-R/resepformer-librimix2spk: direct link, hf CLI and curl.
- Browser
- Download file 1.76 kB
-
https://huggingface.co/Jahmori-R/resepformer-librimix2spk/resolve/main/hyperparams.yaml
- Command line
-
hf download hf://Jahmori-R/resepformer-librimix2spk/hyperparams.yaml
-
curl -L -o hyperparams.yaml https://huggingface.co/Jahmori-R/resepformer-librimix2spk/resolve/main/hyperparams.yaml
1.76 kB
| # ############################################################################ | |
| # Model: RE-SepFormer for source separation | |
| # Dataset: Libri2mix (16k Sample Rate) | |
| # ############################################################################ | |
| # Basic parameters | |
| sample_rate: 16000 | |
| num_spks: 2 | |
| # Encoder parameters | |
| N_encoder_out: 128 | |
| out_channels: 128 | |
| kernel_size: 16 | |
| kernel_stride: 8 | |
| d_ffn: 1024 | |
| # Specifying the network | |
| Encoder: !new:speechbrain.lobes.models.dual_path.Encoder | |
| kernel_size: 16 | |
| out_channels: 128 | |
| # RE-SepFormer specific Transformer Blocks | |
| intra_mdl: | |
| !new:speechbrain.lobes.models.resepformer.SBTransformerBlock_wnormandskip | |
| num_layers: 8 | |
| d_model: 128 | |
| nhead: 8 | |
| d_ffn: 1024 | |
| dropout: 0 | |
| use_positional_encoding: true | |
| norm_before: true | |
| use_norm: true | |
| use_skip: true | |
| mem_mdl: | |
| !new:speechbrain.lobes.models.resepformer.SBTransformerBlock_wnormandskip | |
| num_layers: 8 | |
| d_model: 128 | |
| nhead: 8 | |
| d_ffn: 1024 | |
| dropout: 0 | |
| use_positional_encoding: true | |
| norm_before: true | |
| use_norm: true | |
| use_skip: true | |
| MaskNet: | |
| !new:speechbrain.lobes.models.resepformer.ResourceEfficientSeparator | |
| input_dim: 128 | |
| num_spk: 2 | |
| causal: false | |
| unit: 256 | |
| segment_size: 150 | |
| layer: 2 | |
| mem_type: av | |
| seg_model: | |
| mem_model: | |
| Decoder: !new:speechbrain.lobes.models.dual_path.Decoder | |
| in_channels: 128 | |
| out_channels: 1 | |
| kernel_size: 16 | |
| stride: 8 | |
| bias: false | |
| modules: | |
| encoder: | |
| decoder: | |
| masknet: | |
| pretrainer: !new:speechbrain.utils.parameter_transfer.Pretrainer | |
| loadables: | |
| encoder: !ref <Encoder> | |
| decoder: !ref <Decoder> | |
| masknet: !ref <MaskNet> | |