0.2.0

README.md

@@ -16,12 +16,22 @@ F5 is an evolution of [E2 TTS](https://arxiv.org/abs/2406.18009v2) and improves
 pip install f5-tts-mlx
 ```
 
-## Usage
+## Basic Usage
 
 ```bash
 python -m f5_tts_mlx.generate --text "The quick brown fox jumped over the lazy dog."
 ```
 
+You can also use a pipe to generate speech from the output of another process, for instance from a language model:
+
+```bash
+mlx_lm.generate --model mlx-community/Llama-3.2-1B-Instruct-4bit --verbose false \
+--prompt "Write a concise paragraph explaning wavelets as used in signal processing." \
+| python -m f5_tts_mlx.generate
+```
+
+## Voice Matching
+
 If you want to use your own reference audio sample, make sure it's a mono, 24kHz wav file of around 5-10 seconds:
 
 ```bash
@@ -39,9 +49,9 @@ ffmpeg -i /path/to/audio.wav -ac 1 -ar 24000 -sample_fmt s16 -t 10 /path/to/outp
 
 See [here](./f5_tts_mlx) for more options to customize generation.
 
-—
+## From Python
 
-You can load a pretrained model from Python like this:
+You can load a pretrained model from Python:
 
 ```python
 from f5_tts_mlx.generate import generate

f5_tts_mlx/generate.py

@@ -185,7 +185,8 @@ def generate(
         if output_path is not None:
             sf.write(output_path, np.array(wave), SAMPLE_RATE)
 
-        player.stop()
+        if player is not None:
+            player.stop()
     else:
         start_date = datetime.datetime.now()
 
@@ -229,7 +230,8 @@ def generate(
         if output_path is not None:
             sf.write(output_path, np.array(wave), SAMPLE_RATE)
 
-        player.stop()
+        if player is not None:
+            player.stop()
 
 
 if __name__ == "__main__":

pyproject.toml

@@ -6,7 +6,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "f5-tts-mlx"
-version = "0.1.9"
+version = "0.2.0"
 authors = [{name = "Lucas Newman", email = "[email protected]"}]
 license = {text = "MIT"}
 description = "F5-TTS - MLX"