| { |
| "root": "pretrained_models", |
| "structure": { |
| "files": [ |
| { |
| "path": "pretrained_models/denoiser_model.onnx", |
| "info": "Audio denoising model (DeepFilterNet)" |
| } |
| ], |
| "ckpts": { |
| "autoregressive": { |
| "path": "pretrained_models/ckpts/autoregressive", |
| "description": "Autoregressive neural codec editing model and its dependencies", |
| "files": [ |
| { |
| "path": "pretrained_models/ckpts/autoregressive/config.json", |
| "info": "Model architecture and hyperparameter configuration for the autoregressive editing model" |
| }, |
| { |
| "path": "pretrained_models/ckpts/autoregressive/multilingual_330M.pth", |
| "info": "Main weights of the multilingual autoregressive codec editing model (~330M parameters), used when Edit Model=autoregressive" |
| }, |
| { |
| "path": "pretrained_models/ckpts/autoregressive/encodec_4cb2048_giga.th", |
| "info": "Neural codec encoder (AudioTokenizer) with 4 codebooks × 2048 codewords, used to decode discrete codes into 16kHz waveforms" |
| }, |
| { |
| "path": "pretrained_models/ckpts/autoregressive/dac_SR_8codes_2048_hop960_speech.pth", |
| "info": "DAC super-resolution model (AudioSR), used to reconstruct audio from 16kHz codec to 48kHz or target sample rate for the AR backend" |
| } |
| ] |
| }, |
| "multilingual_grl": { |
| "path": "pretrained_models/ckpts/multilingual_grl", |
| "description": "Main LEMAS-TTS model (multilingual_grl)", |
| "files": [ |
| { |
| "path": "pretrained_models/ckpts/multilingual_grl/multilingual_grl.safetensors", |
| "info": "Unconditional/text-conditioned non-autoregressive model weights with GRL, supporting multilingual TTS and editing (default Edit Model in Gradio)" |
| } |
| ] |
| }, |
| "multilingual_prosody": { |
| "path": "pretrained_models/ckpts/multilingual_prosody", |
| "description": "non-autoregressive variant with an additional prosody encoder", |
| "files": [ |
| { |
| "path": "pretrained_models/ckpts/multilingual_prosody/multilingual_prosody.safetensors", |
| "info": "Multilingual model weights with global prosody conditioning enabled (selectable in the model menu)" |
| } |
| ] |
| }, |
| "prosody_encoder": { |
| "path": "pretrained_models/ckpts/prosody_encoder", |
| "description": "Pretssel / UnitY2-style prosody encoder used by the non-autoregressive prosody backend", |
| "files": [ |
| { |
| "path": "pretrained_models/ckpts/prosody_encoder/pretssel_cfg.json", |
| "info": "Architecture configuration for the Pretssel/UnitY2 prosody encoder (dimensions, number of layers, etc.)" |
| }, |
| { |
| "path": "pretrained_models/ckpts/prosody_encoder/prosody_encoder_UnitY2.pt", |
| "info": "Prosody encoder weights, used to extract global prosody embeddings from reference audio" |
| } |
| ] |
| }, |
| "vocos-mel-24khz": { |
| "path": "pretrained_models/ckpts/vocos-mel-24khz", |
| "description": "Vocos neural vocoder (mel → 24kHz waveform)", |
| "files": [ |
| { |
| "path": "pretrained_models/ckpts/vocos-mel-24khz/config.yaml", |
| "info": "Vocos vocoder configuration defining mel feature dimensions and network architecture" |
| }, |
| { |
| "path": "pretrained_models/ckpts/vocos-mel-24khz/pytorch_model.bin", |
| "info": "Main Vocos vocoder weights, used to decode mel features in the CFM backend" |
| }, |
| { |
| "path": "pretrained_models/ckpts/vocos-mel-24khz/README.md", |
| "info": "Documentation for the vocoder (origin, usage, and notes)" |
| } |
| ] |
| } |
| }, |
| "data": { |
| "multilingual_grl": { |
| "path": "pretrained_models/data/multilingual_grl", |
| "description": "Text vocabulary for the multilingual_grl model", |
| "files": [ |
| { |
| "path": "pretrained_models/data/multilingual_grl/vocab.txt", |
| "info": "phone vocabulary corresponding to the text embeddings of the multilingual_grl model" |
| } |
| ] |
| }, |
| "multilingual_prosody": { |
| "path": "pretrained_models/data/multilingual_prosody", |
| "description": "Text vocabulary for the multilingual_prosody model", |
| "files": [ |
| { |
| "path": "pretrained_models/data/multilingual_prosody/vocab.txt", |
| "info": "Shared text vocabulary used by the multilingual_prosody model" |
| } |
| ] |
| } |
| }, |
| "demos": { |
| "root": "pretrained_models/demos", |
| "files": [ |
| { |
| "path": "pretrained_models/demos/test.wav", |
| "info": "Simple test audio used for quick validation of gradio script" |
| } |
| ], |
| "lemas_edit_test": { |
| "path": "pretrained_models/demos/lemas_edit_test", |
| "description": "Audio samples and alignment annotations for LEMAS-Edit demos", |
| "subdirs": { |
| "vocals": { |
| "path": "pretrained_models/demos/lemas_edit_test/vocals", |
| "files": [ |
| { |
| "path": "pretrained_models/demos/lemas_edit_test/vocals/en_AUD0000000214_S0001522.mp3", |
| "info": "English demo audio used for AR/NAR editing examples" |
| }, |
| { |
| "path": "pretrained_models/demos/lemas_edit_test/vocals/zh_emilia_zh_0008385782.mp3", |
| "info": "Chinese demo audio used for multilingual editing examples" |
| } |
| ] |
| }, |
| "align": { |
| "path": "pretrained_models/demos/lemas_edit_test/align", |
| "files": [ |
| { |
| "path": "pretrained_models/demos/lemas_edit_test/align/en_AUD0000000214_S0001522.json", |
| "info": "MMS alignment JSON for the English demo, including intervals, words, and modified_index used for editing" |
| }, |
| { |
| "path": "pretrained_models/demos/lemas_edit_test/align/zh_emilia_zh_0008385782.json", |
| "info": "MMS alignment JSON for the Chinese demo" |
| } |
| ] |
| } |
| } |
| } |
| }, |
| "uvr5": { |
| "path": "pretrained_models/uvr5", |
| "description": "Kim Vocal UVR5 models and configurations (used for denoising)", |
| "files": [ |
| { |
| "path": "pretrained_models/uvr5/Kim_Vocal_1.onnx", |
| "info": "Main UVR5 model (ONNX format) for vocal/accompaniment separation and denoising" |
| }, |
| { |
| "path": "pretrained_models/uvr5/MDX-Net-Kim-Vocal1.json", |
| "info": "UVR5 model architecture and inference configuration (channels, frame length, etc.)" |
| }, |
| { |
| "path": "pretrained_models/uvr5/model_data.json", |
| "info": "UVR5 metadata including presets, model list, and default parameters" |
| }, |
| { |
| "path": "pretrained_models/uvr5/model_name_mapper.json", |
| "info": "Mapping from internal UVR5 model names to human-readable names for frontend selection" |
| } |
| ] |
| }, |
| "whisperx": { |
| "path": "pretrained_models/whisperx", |
| "description": "WhisperX VAD and segmentation model assets", |
| "files": [ |
| { |
| "path": "pretrained_models/whisperx/whisperx-vad-segmentation.bin", |
| "info": "WhisperX voice activity detection (VAD) weights used for long-audio segmentation and ASR alignment assistance" |
| }, |
| { |
| "path": "pretrained_models/whisperx/whisperx-vad-segmentation.bak", |
| "info": "Backup or legacy version of the VAD model, kept for safety" |
| } |
| ] |
| } |
| } |
| } |
|
|
