Update docs (coqui-ai#2919)

Author: erogol

docs/requirements.txt

@@ -1,6 +1,6 @@
 furo
 myst-parser == 2.0.0
-sphinx == 7.0.1
+sphinx == 7.2.5
 sphinx_inline_tabs
 sphinx_copybutton
 linkify-it-py

docs/source/docker_images.md

@@ -43,7 +43,7 @@ Start the container and get a shell inside it.
 ```bash
 docker run --rm -it -p 5002:5002 --entrypoint /bin/bash ghcr.io/coqui-ai/tts-cpu
 python3 TTS/server/server.py --list_models #To get the list of available models
-python3 TTS/server/server.py --model_name tts_models/en/vctk/vits 
+python3 TTS/server/server.py --model_name tts_models/en/vctk/vits
 ```
 
 ### GPU version

docs/source/implementing_a_new_model.md

@@ -36,7 +36,7 @@
     There is also the `callback` interface by which you can manipulate both the model and the `Trainer` states. Callbacks give you
     an infinite flexibility to add custom behaviours for your model and training routines.
 
-    For more details, see {ref}`BaseTTS <Base TTS Model>` and :obj:`TTS.utils.callbacks`.
+    For more details, see {ref}`BaseTTS <Base tts Model>` and :obj:`TTS.utils.callbacks`.
 
 6. Optionally, define `MyModelArgs`.
 
@@ -204,5 +204,3 @@ class MyModel(BaseTTS):
         pass
 
 ```
-
-

docs/source/main_classes/model_api.md

@@ -5,18 +5,18 @@ Model API provides you a set of functions that easily make your model compatible
 ## Base TTS Model
 
 ```{eval-rst}
-.. autoclass:: TTS.model.BaseModel
+.. autoclass:: TTS.model.BaseTrainerModel
     :members:
 ```
 
-## Base `tts` Model
+## Base tts Model
 
 ```{eval-rst}
 .. autoclass:: TTS.tts.models.base_tts.BaseTTS
     :members:
 ```
 
-## Base `vocoder` Model
+## Base vocoder Model
 
 ```{eval-rst}
 .. autoclass:: TTS.vocoder.models.base_vocoder.BaseVocoder

docs/source/models/bark.md

@@ -91,12 +91,6 @@ tts --model_name  tts_models/multilingual/multi-dataset/bark \
     :members:
 ```
 
-## BarkArgs
-```{eval-rst}
-.. autoclass:: TTS.tts.models.bark.BarkArgs
-    :members:
-```
-
 ## Bark Model
 ```{eval-rst}
 .. autoclass:: TTS.tts.models.bark.Bark