Upload 5 files
Browse files- README.md +14 -0
- sovits4.1-Latest_44k/G_101600.pth +3 -0
- sovits4.1-Latest_44k/config.json +107 -0
- sovits4.1-Latest_44k/config.yaml +51 -0
- sovits4.1-Latest_44k/model_196000.pt +3 -0
README.md
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- **Model type:** [so-vits-svc 3.0 48kHz](https://github.com/svc-develop-team/so-vits-svc/tree/3.0-48k)、[so-vits-svc 4.0](https://github.com/svc-develop-team/so-vits-svc)
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- **Demo:** [SPACE: AI岁己(歌声变声器)](https://huggingface.co/spaces/Miuzarte/SUI-svc-3.0)、[SPACE: AI岁己(歌声变声器)第二代](https://huggingface.co/spaces/Miuzarte/SUI-svc-4.0)
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### pth文件名的训练步数是程序按学习率等超参数得出的步数,onnx文件名的步数为实际训练步数
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|sovits3_v1|Base/G_1000000.pth|Singing/G_1M111000.pth|Singing/G_100000.pth|
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- **Model type:** [so-vits-svc 3.0 48kHz](https://github.com/svc-develop-team/so-vits-svc/tree/3.0-48k)、[so-vits-svc 4.0](https://github.com/svc-develop-team/so-vits-svc)
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- **Demo:** [SPACE: AI岁己(歌声变声器)](https://huggingface.co/spaces/Miuzarte/SUI-svc-3.0)、[SPACE: AI岁己(歌声变声器)第二代](https://huggingface.co/spaces/Miuzarte/SUI-svc-4.0)
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### 新模型:分子4.1-Latest
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跟几个旧的4.0一样的训练集,底模比之前好了不少炼起来快了很多
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算力提供:[米玖澪](https://space.bilibili.com/365980549)
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没导出onnx,去用 [Google Colab](https://colab.research.google.com/github/svc-develop-team/so-vits-svc/blob/4.1-Stable/sovits4_for_colab.ipynb) 来推理挺方便的
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|sovits4.1-Latest|G_101600.pth|model_196000.pt|
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|-:|:-:|:-:|
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|备注|主模型|浅扩撒模型|
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### 旧模型:
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### pth文件名的训练步数是程序按学习率等超参数得出的步数,onnx文件名的步数为实际训练步数
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|sovits3_v1|Base/G_1000000.pth|Singing/G_1M111000.pth|Singing/G_100000.pth|
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sovits4.1-Latest_44k/G_101600.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:79be9b852f8b864d1d399cc4285e9d7ecf1f2aa4cd74b2090b9f1ac4bbbbff30
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size 627915739
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sovits4.1-Latest_44k/config.json
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{
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"train": {
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"log_interval": 200,
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"eval_interval": 800,
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"seed": 1234,
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"epochs": 10000,
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"learning_rate": 0.0001,
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"betas": [
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0.8,
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0.99
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],
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"eps": 1e-09,
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"batch_size": 25,
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"fp16_run": true,
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"half_type": "fp16",
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"lr_decay": 0.999875,
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"segment_size": 10240,
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"init_lr_ratio": 1,
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"warmup_epochs": 0,
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"c_mel": 45,
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"c_kl": 1.0,
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"use_sr": true,
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"max_speclen": 512,
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"port": "8001",
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"keep_ckpts": 3,
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"all_in_mem": false,
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"vol_aug": true
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},
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"data": {
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"training_files": "filelists/train.txt",
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"validation_files": "filelists/val.txt",
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"max_wav_value": 32768.0,
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"sampling_rate": 44100,
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"filter_length": 2048,
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"hop_length": 512,
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"win_length": 2048,
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"n_mel_channels": 80,
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"mel_fmin": 0.0,
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"mel_fmax": 22050,
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"unit_interpolate_mode": "nearest"
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},
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"model": {
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"inter_channels": 192,
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"hidden_channels": 192,
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"filter_channels": 768,
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"n_heads": 2,
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"n_layers": 6,
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"kernel_size": 3,
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"p_dropout": 0.1,
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"resblock": "1",
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"resblock_kernel_sizes": [
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3,
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],
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"resblock_dilation_sizes": [
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],
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"upsample_rates": [
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],
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"upsample_initial_channel": 512,
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"upsample_kernel_sizes": [
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],
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"n_layers_q": 3,
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"n_layers_trans_flow": 3,
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"n_flow_layer": 4,
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"use_spectral_norm": false,
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"gin_channels": 768,
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"ssl_dim": 768,
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"n_speakers": 1,
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"vocoder_name": "nsf-hifigan",
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"speech_encoder": "vec768l12",
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"speaker_embedding": false,
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"vol_embedding": true,
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"use_depthwise_conv": false,
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"flow_share_parameter": false,
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"use_automatic_f0_prediction": true,
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"use_transformer_flow": false
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},
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"spk": {
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"sui": 0
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}
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}
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sovits4.1-Latest_44k/config.yaml
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data:
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block_size: 512
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cnhubertsoft_gate: 10
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duration: 2
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encoder: vec768l12
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encoder_hop_size: 320
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encoder_out_channels: 768
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encoder_sample_rate: 16000
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extensions:
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- wav
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sampling_rate: 44100
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training_files: filelists/train.txt
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unit_interpolate_mode: nearest
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validation_files: filelists/val.txt
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device: cuda
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env:
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expdir: logs/44k/diffusion
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gpu_id: 0
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infer:
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method: dpm-solver++
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speedup: 10
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model:
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k_step_max: 200
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n_chans: 512
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n_hidden: 256
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n_layers: 20
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n_spk: 1
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timesteps: 1000
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type: Diffusion
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use_pitch_aug: true
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spk:
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sui: 0
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train:
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amp_dtype: fp32
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batch_size: 48
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cache_all_data: true
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cache_device: cpu
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cache_fp16: true
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decay_step: 100000
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epochs: 100000
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gamma: 0.5
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interval_force_save: 5000
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interval_log: 10
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interval_val: 2000
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lr: 0.0001
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num_workers: 4
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save_opt: false
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weight_decay: 0
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vocoder:
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ckpt: pretrain/nsf_hifigan/model
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type: nsf-hifigan
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sovits4.1-Latest_44k/model_196000.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:612f199e6227e62b56c83c1c9c566c700e1290cfb3cbb5557a5c9a4456b31dab
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size 220893960
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