A fine-tuned version of Qwen3-TTS-12Hz-1.7B-Base trained on a custom speaker dataset using supervised fine-tuning (SFT).
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Quellenbeschreibung
A fine-tuned version of Qwen3-TTS-12Hz-1.7B-Base trained on a custom speaker dataset using supervised fine-tuning (SFT).
pip install qwen-tts torch torchaudio
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1 QuelleVerifiziert 13. Sept.
Modellartefakte
1 ArtefaktQuellenauszüge
2 Auszüge--- license: apache-2.0 base_model: Qwen/Qwen3-TTS-12Hz-1.7B-Base tags: - text-to-speech - qwen3-tts - fine-tuned - voice-cloning language: - en --- # Qwen3-TTS — Custom Voice Clone A fine-tuned version of [Qwen3-TTS-12Hz-1.7B-Base](https://huggingface.co/Qwen/Qwen3-TTS-12Hz-1.7B-Base) trained on a custom speaker dataset using supervised fine-tuning (SFT). --- ## Requirements ```bash pip install qwen-tts torch torchaudio ``` ## Usage ```python import torch import soundfile as sf from qwen_tts import Qwen3TTSModel tts = Qwen3TTSModel.from_pretrained( "thunk6/qwen3-tts-custom-voice", device_map="cuda:0", dtype=torch.bfloat16, ) wavs, sr = tts.generate_custom_voice( text="Hello, this is my cloned voice.", speaker="my_custom_voice", ) sf.write("output.wav", wavs[0], sr) ``` ## Training Details | Setting | Value | |---|---| | Base model | Qwen3-TTS-12Hz-1.7B-Base | | Fine-tuning method | SFT | | Learning rate | 2e-6 | | Batch size | 4 | | Epochs | 10 | | Hardware | A100 80GB |
import torch
import soundfile as sf
from qwen_tts import Qwen3TTSModel
tts = Qwen3TTSModel.from_pretrained(
"thunk6/qwen3-tts-custom-voice",
device_map="cuda:0",
dtype=torch.bfloat16,
)
wavs, sr = tts.generate_custom_voice(
text="Hello, this is my cloned voice.",
speaker="my_custom_voice",
)
sf.write("output.wav", wavs[0], sr)
| Setting | Value |
|---|---|
| Base model | Qwen3-TTS-12Hz-1.7B-Base |
| Fine-tuning method | SFT |
| Learning rate | 2e-6 |
| Batch size | 4 |
| Epochs | 10 |
| Hardware | A100 80GB |
Source context: 11 downloads · 0 likes · Pipeline text-to-speech · Repo thunk6/qwen3-tts-custom-voice