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Christopher Woodall 2023-01-13 07:53:15 -05:00
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@ -11,7 +11,7 @@ An unofficial PyTorch implementation of [VALL-E](https://valle-demo.github.io/),
### Install with pip ### Install with pip
``` ```
pip install git+https://github.com/enhuiz/vall-e pip install --editable .
``` ```
### Clone ### Clone
@ -29,13 +29,13 @@ Note that the code is only tested under `Python 3.10.7`.
2. Quantize the data: 2. Quantize the data:
``` ```
python -m vall_e.emb.qnt data/your_data valle-quantize data/your_data
``` ```
3. Generate phonemes based on the text: 3. Generate phonemes based on the text:
``` ```
python -m vall_e.emb.g2p data/your_data valle-phonemes data/your_data
``` ```
4. Customize your configuration by creating `config/your_data/ar.yml` and `config/your_data/nar.yml`. Refer to the example configs in `config/test` and `vall_e/config.py` for details. You may choose different model presets, check `vall_e/vall_e/__init__.py`. 4. Customize your configuration by creating `config/your_data/ar.yml` and `config/your_data/nar.yml`. Refer to the example configs in `config/test` and `vall_e/config.py` for details. You may choose different model presets, check `vall_e/vall_e/__init__.py`.
@ -43,7 +43,7 @@ python -m vall_e.emb.g2p data/your_data
5. Train the AR or NAR model using the following scripts: 5. Train the AR or NAR model using the following scripts:
``` ```
python -m vall_e.train yaml=config/your_data/ar_or_nar.yml valle-train yaml=config/your_data/ar_or_nar.yml
``` ```
## TODO ## TODO