MAGO PersonaPlex emotion finetune

Full-duplex speech-to-speech LoRA finetune of PersonaPlex, merged into one model.safetensors. Trained on duplex conversations whose speech was synthesized with Boson AI Higgs Audio v3 TTS 4B (Higgs TTS 3). The agent was trained to follow:

Answer with a {emotion} tone.

where {emotion} is happy, sad, angry, or neutral.

This repo is not affiliated with NVIDIA or Boson AI. See NOTICE and LICENSE.

Use

Same stack as PersonaPlex. model.safetensors replaces the base LM weights. Mimi, the text tokenizer, and voice prompts still come from nvidia/personaplex-7b-v1 unless those files are also in this repo.

Accept the PersonaPlex license at https://huggingface.co/nvidia/personaplex-7b-v1 before the base files will download.

Offline, one WAV in and one WAV out. Download the LM weights from mago-ai/emotionplex-7b first. Mimi, the text tokenizer, and voice prompts still come from nvidia/personaplex-7b-v1.

hf download mago-ai/emotionplex-7b model.safetensors --local-dir weights

python -m moshi.offline \
  --moshi-weight weights/model.safetensors \
  --hf-repo nvidia/personaplex-7b-v1 \
  --voice-prompt NATF2.pt \
  --text-prompt "Answer with a sad tone." \
  --input-wav user.wav \
  --output-wav agent.wav \
  --output-text out.json

For the web server, download the same weights, plus the PersonaPlex web UI (dist.tgz). --hf-repo nvidia/personaplex-7b-v1 still supplies Mimi, the tokenizer, and voice prompts.

hf download mago-ai/emotionplex-7b model.safetensors --local-dir weights
hf download nvidia/personaplex-7b-v1 dist.tgz --local-dir weights
tar -xzf weights/dist.tgz -C weights

python -m moshi.server \
  --moshi-weight weights/model.safetensors \
  --hf-repo nvidia/personaplex-7b-v1 \
  --static weights/dist

moshi is the PersonaPlex server package (personaplex/moshi). Voice prompts such as NATF2.pt come from voices.tgz on nvidia/personaplex-7b-v1.

What this is

LoRA rank 512, scaling 2, merged in bfloat16 into PersonaPlex 7B. The text prompt is the system prompt PersonaPlex reads before the conversation.

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