From 20cf8d7365352d1336e152037b88623696e8556f Mon Sep 17 00:00:00 2001 From: laurent Date: Thu, 3 Jul 2025 07:43:56 +0200 Subject: [PATCH] Collapsible sections. --- README.md | 30 ++++++++++++++++++++++-------- 1 file changed, 22 insertions(+), 8 deletions(-) diff --git a/README.md b/README.md index 364d6c2..73df270 100644 --- a/README.md +++ b/README.md @@ -44,7 +44,8 @@ Here is how to choose which one to use: MLX is Apple's ML framework that allows you to use hardware acceleration on Apple silicon. If you want to run the model on a Mac or an iPhone, choose the MLX implementation. -### PyTorch implementation +
+PyTorch implementation Hugging Face @@ -99,8 +100,10 @@ In the heart of an ancient forest, where the trees whispered secrets of the past Apart from nudging the model for a specific spelling of a word, other potential use-cases include speaker adaptation and steering the model towards a specific formatting style or even a language. However, please bear in mind that is an experimental feature and its behavior is very sensitive to the prompt provided. +
-### Rust server +
+Rust server Hugging Face @@ -143,8 +146,10 @@ The script limits the decoding speed to simulates real-time processing of the au Faster processing can be triggered by setting the real-time factor, e.g. `--rtf 1000` will process the data as fast as possible. +
-### Rust standalone +
+Rust standalone Hugging Face @@ -157,8 +162,10 @@ cargo run --features cuda -r -- audio/bria.mp3 ``` You can get the timestamps by adding the `--timestamps` flag, and see the output of the semantic VAD by adding the `--vad` flag. +
-### MLX implementation +
+MLX implementation Hugging Face @@ -187,6 +194,7 @@ python scripts/stt_from_mic_mlx.py The MLX models can also be used in swift using the [moshi-swift codebase](https://github.com/kyutai-labs/moshi-swift), the 1b model has been tested to work fine on an iPhone 16 Pro. +
## Kyutai Text-to-Speech @@ -200,7 +208,8 @@ We provide different implementations of Kyutai TTS for different use cases. Here - Rust: for production. If you want to serve Kyutai TTS in a production setting, use our Rust server. Our robust Rust server provides streaming access to the model over websockets. We use this server to run Unmute. - MLX: for on-device inference on iPhone and Mac. MLX is Apple's ML framework that allows you to use hardware acceleration on Apple silicon. If you want to run the model on a Mac or an iPhone, choose the MLX implementation. -### PyTorch implementation +
+PyTorch implementation Open In Colab @@ -219,12 +228,16 @@ python scripts/tts_pytorch.py text_to_say.txt audio_output.wav This requires the [moshi package](https://pypi.org/project/moshi/), which can be installed via pip. If you have [uv](https://docs.astral.sh/uv/) installed, you can skip the installation step and just prefix the command above with `uvx --with moshi`. +
-### Rust server +
+Rust server Example coming soon. +
-### MLX implementation +
+MLX implementation [MLX](https://ml-explore.github.io/mlx/build/html/index.html) is Apple's ML framework that allows you to use hardware acceleration on Apple silicon. @@ -243,6 +256,7 @@ python scripts/tts_mlx.py text_to_say.txt audio_output.wav This requires the [moshi-mlx package](https://pypi.org/project/moshi-mlx/), which can be installed via pip. If you have [uv](https://docs.astral.sh/uv/) installed, you can skip the installation step and just prefix the command above with `uvx --with moshi-mlx`. +
## License @@ -262,4 +276,4 @@ pip install pre-commit pre-commit install ``` -If you're using `uv`, you can replace the two commands with `uvx pre-commit install`. \ No newline at end of file +If you're using `uv`, you can replace the two commands with `uvx pre-commit install`.