ml-explore / ml-explore/mlx-examples
[Model Request] Porting Nvidia PersonaPlex-7B (Moshi architecture) & Mimi Codec
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- Dominant language
- Python
- Stars
- 9k
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Description
Hi team,
With the recent release of Nvidia PersonaPlex-7B-v1, which is based on the Moshi architecture (Kyutai), I am interested in working on a port for MLX to enable full-duplex speech-to-speech on Apple Silicon.
Since this is a complex architecture, I wanted to open this issue to track progress and gauge community interest.
The Roadmap:
- Port the Mimi Codec: This is the neural audio codec used by Moshi/PersonaPlex. It requires converting the streaming convolutional/LSTM encoder-decoder to
mlx.nn. - Port the LM Architecture: PersonaPlex uses a specific architecture (interleaved text/audio tokens) potentially based on Helium or Llama, adapted for streaming generation.
- Streaming Loop: Implementing the real-time input/output loop.
I plan to start working on this in a separate repository. If anyone has already started looking into Moshi or Mimi specifically, please let me know to avoid duplicate work!
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reviewing the proposed Mimi Codec, Moshi architecture, and PersonaPlex-7B components described in the issue. The payload names no repository files, tests, or entry points; done would require a working MLX port covering the codec, model architecture, and streaming loop, with work planned in a separate repository.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- audio-video-rtc, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 25/100