mirror of https://github.com/coqui-ai/TTS.git
Update docs
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@ -1,6 +1,6 @@
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furo
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myst-parser == 2.0.0
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sphinx == 7.0.1
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sphinx == 7.2.5
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sphinx_inline_tabs
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sphinx_copybutton
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linkify-it-py
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@ -43,7 +43,7 @@ Start the container and get a shell inside it.
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```bash
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docker run --rm -it -p 5002:5002 --entrypoint /bin/bash ghcr.io/coqui-ai/tts-cpu
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python3 TTS/server/server.py --list_models #To get the list of available models
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python3 TTS/server/server.py --model_name tts_models/en/vctk/vits
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python3 TTS/server/server.py --model_name tts_models/en/vctk/vits
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```
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### GPU version
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@ -36,7 +36,7 @@
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There is also the `callback` interface by which you can manipulate both the model and the `Trainer` states. Callbacks give you
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an infinite flexibility to add custom behaviours for your model and training routines.
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For more details, see {ref}`BaseTTS <Base TTS Model>` and :obj:`TTS.utils.callbacks`.
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For more details, see {ref}`BaseTTS <Base tts Model>` and :obj:`TTS.utils.callbacks`.
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6. Optionally, define `MyModelArgs`.
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@ -204,5 +204,3 @@ class MyModel(BaseTTS):
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pass
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```
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@ -5,18 +5,18 @@ Model API provides you a set of functions that easily make your model compatible
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## Base TTS Model
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```{eval-rst}
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.. autoclass:: TTS.model.BaseModel
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.. autoclass:: TTS.model.BaseTrainerModel
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:members:
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```
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## Base `tts` Model
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## Base tts Model
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```{eval-rst}
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.. autoclass:: TTS.tts.models.base_tts.BaseTTS
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:members:
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```
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## Base `vocoder` Model
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## Base vocoder Model
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```{eval-rst}
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.. autoclass:: TTS.vocoder.models.base_vocoder.BaseVocoder
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@ -91,12 +91,6 @@ tts --model_name tts_models/multilingual/multi-dataset/bark \
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:members:
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```
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## BarkArgs
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```{eval-rst}
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.. autoclass:: TTS.tts.models.bark.BarkArgs
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:members:
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```
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## Bark Model
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```{eval-rst}
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.. autoclass:: TTS.tts.models.bark.Bark
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