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--- |
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tags: |
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- DiffSVC |
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- pre-trained_model |
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- basemodel |
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- diff-svc |
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license: "gpl" |
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datasets: |
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- 512rc_50k |
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- 512rc_80k |
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- 512rc_100k |
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--- |
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**English** | [简体中文](./README_CN.md) |
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# DiffSVCBaseModel |
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A Diff-SVC base model for all kind of voice |
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## Have a preview~ |
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| Raw | Inference with Nahida model | |
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| -------------- | ------------------------------------ | |
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| [Raw](https://huggingface.co/HuanLin/DiffSVCBaseModel/resolve/main/gouzhiqishi.wav) | [Result](https://huggingface.co/HuanLin/DiffSVCBaseModel/resolve/main/gouzhiqishi_-4key_nahida_384_20_348k_0x.flac) | |
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## How to use? |
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1. Choose and download this model |
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2. Fill your config and put your datasets into ```(diffsvc-root)/data/raw/{speaker_name}/``` |
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3. Throw this base model(only .ckpt file) into ```(diffsvc-root)/checkpoints/{speaker_name}``` |
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4. Then start preprocessing and training as usual |
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## How much data do you use? |
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I use 2 public datasets(opencpop ,m4singer),40h+ audio in total. |
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## I want to train my own base model! |
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OK, you can download [this bianry file](./BaseModelBinary.tar.gz). |
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## Download |
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** Please choose a model that matches your config.yaml or config_nsf.yaml ** |
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| Version | URL | Reference value of lr | |
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| -------------- | ------------------------------------ | --------------------- | |
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| 384rc,50k_step | [Click here](./384rc_50k_step.zip) | 0.0016 | |
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| 384rc,80k_step | [Click here](./384rc_80k_step.zip) | 0.0032 | |
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| 384rc,100k_step | [Click here](./384rc_100k_step.zip) | 0.0032 | |
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> rc: residual_channels |
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More coming soon... |
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## Repos |
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| Repo | URL | |
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| -------------------------------------------------------- | ------------------------------------------------------------------- | |
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| Diff-SVC | [Click here](https://github.com/prophesier/diff-svc) | |
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| 44.1KHz Vocoder | [Click here](https://openvpi.github.io/vocoders) | |
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| M4Singer | [Click here](https://github.com/M4Singer/M4Singer) | |
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| OpenCPOP | [Click here](https://github.com/wenet-e2e/opencpop) | |
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| Pre-trained_Models(My friend's pre-trained model) | [Click here](https://huggingface.co/Erythrocyte/Pre-trained_Models) | |
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