---
library_name: transformers
license: other
license_name: nvidia-open-model-license
license_link: https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-open-model-license/
base_model:
- Qwen/Qwen3-8B
- nvidia/personaplex-7b-v1
base_model_relation: merge
tags:
- kmoshi
- moshi
- full-duplex
- speech
- korean
---

# KMoshi (init)

An assembled checkpoint that couples the **Qwen3-8B** temporal backbone (Korean-capable
text LLM) with the **PersonaPlex** audio stack (Mimi codec, depth decoder with dep_q=16,
and 16 audio input embeddings), toward a Korean full-duplex spoken dialogue model.

> Status: **before coupling training.** The backbone was swapped from Helium to Qwen3-8B,
> so the audio stack is not yet aligned with it — **audio output is expected to be noise**.
> The text stream is already fluent (evidence that the backbone transplant is numerically
> correct). Background and assembly code: https://github.com/un1876/k-moshi

## Usage

    # pip install "git+https://github.com/un1876/k-moshi.git@main"  (not in upstream transformers)
    from transformers.models.kmoshi.modeling_kmoshi import KmoshiForConditionalGeneration
    model = KmoshiForConditionalGeneration.from_pretrained("spidyun/kmoshi")

## Attribution / Licenses

- Backbone weights: [Qwen/Qwen3-8B](https://huggingface.co/Qwen/Qwen3-8B) — Apache-2.0
- Audio stack (Mimi codec, depth decoder, audio input embeddings):
  [nvidia/personaplex-7b-v1](https://huggingface.co/nvidia/personaplex-7b-v1) —
  NVIDIA Open Model License (+ CC-BY-4.0). See `LICENSE` / `Notice` in this repository.
- The Mimi codec is byte-identical to stock Moshi (kyutai, CC-BY-4.0).
- `depth_decoder.text_embed_tokens` is re-initialized for the new tokenizer vocab
  (151936) and belongs to the coupling-training stage.