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---
license: cc-by-nc-sa-4.0
base_model: macminix/qwen3_voice_design_t1
pipeline_tag: text-to-speech
library_name: transformers
language:
- en
tags:
- tts
- qwen
- qwen3
- qwen3-tts
- voice-design
- merged-lora
- fine-tuned
- audio
---
# ckpt-600 β€” merged
Self-contained snapshot of [`macminix/qwen3_voice_design_t1`](https://huggingface.co/macminix/qwen3_voice_design_t1)
with the **ckpt-600** LoRA adapter folded into the Talker weights.
No PEFT layers at runtime β€” load directly with `Qwen3TTSModel.from_pretrained`.
## Quick start
```python
from qwen_tts import Qwen3TTSModel
wrap = Qwen3TTSModel.from_pretrained("<this-repo-id>")
wavs, sr = wrap.generate_voice_design(
text="Hello, this is a test.",
instruct="A young adult female speaker speaks calmly at a normal pace.",
language="english",
temperature=0.9, top_p=1.0, top_k=50,
repetition_penalty=1.05, max_new_tokens=600,
)
```
## Repository layout
Same shape as the upstream macminix repo:
- `config.json`, `model.safetensors` β€” Qwen3-TTS Talker + Code Predictor (merged)
- `speech_tokenizer/` β€” 12.5 fps Γ— 16 codebook neural codec (unchanged)
- `tokenizer.*`, `vocab.json`, `merges.txt`, `added_tokens.json`,
`special_tokens_map.json` β€” Qwen2 BPE tokenizer
- `generation_config.json`, `preprocessor_config.json`
- `vocence_config.yaml`, `chute_config.yml` β€” runtime + Chutes deploy hints
You can drop your own `miner.py` into this repo (same contract as macminix's:
class `Miner` with `__init__(path_hf_repo: Path)`, `warmup()`,
`generate_wav(instruction, text)` β†’ `(np.ndarray, int)`); the standard
Vocence chute wrapper will load this model unchanged.
## Provenance
See [`merge_info.json`](merge_info.json) for the exact base path, adapter
path, LoRA hyperparameters, and merge timestamp.