e3group-research/enderv1.0

E3 Voice4 / Jaiden — Qwen3-TTS 0.6B direct fine-tune

This is the ear-selected epoch-0 full fine-tune of Qwen/Qwen3-TTS-12Hz-0.6B-Base for the E3 Voice4 single-speaker voice. The embedded speaker is exposed as speaker_test; inference does not require reference audio.

The checkpoint was selected from five fixed-seed draws. The preferred output was draw 1 (seed 43), chosen for its balance of speaker identity and expressive range. This replaces the older Vivian/Fish-distilled weights previously on the repository's main branch. Historical models remain available through the repository's v1–v5 tags and commit history.

Quickstart

pip install -U qwen-tts soundfile

import soundfile as sf
import torch
from qwen_tts import Qwen3TTSModel

model = Qwen3TTSModel.from_pretrained(
    "e3group-research/enderv1.0",
    device_map="cuda:0",
    dtype=torch.bfloat16,
)

torch.manual_seed(43)
wavs, sample_rate = model.generate_custom_voice(
    text="This is a test of the E3 Voice4 checkpoint.",
    speaker="speaker_test",
    language="english",
)
sf.write("voice4.wav", wavs[0], sample_rate)

The only configured speaker key is speaker_test (speaker slot 3000).

Training recipe

• Base model: Qwen3-TTS 12 Hz 0.6B Base
• Method: single-stage full fine-tune, not LoRA or teacher distillation
• Data: 130 single-speaker speech clips, 16.56 minutes total
• Retained checkpoint: epoch 0 (65 optimizer steps)
• Learning rate: 2e-5, with 50 warmup steps
• Objective: codec-0 cross entropy + 0.3 × sub-talker loss
• Embedded speaker: slot 3000, populated from the training reference voice

history.json records the complete eight-epoch training run. Only epoch 0 was retained for this release; later epochs were rejected because they overfit and could produce severe duration runaway.

Selection measurements

For the selected seed-43 evaluation draw:

Measurement	Value
Speaker similarity vs. internal reference	0.9261
F0 p10–p90 range	12.45 semitones
F0 median	246.83 Hz
Duration	22.78 seconds
Speaking rate	187 WPM

These are measurements for the selected generation, not aggregate benchmark results. Generation is stochastic and results vary with text and seed.

Integrity

• model.safetensors SHA-256: 54f399102bdfc0b55e5c2ffa7fd1d3eb3d68cae4a516e151cbe6df8d01e96b7a
• speech_tokenizer/model.safetensors SHA-256: 836b7b357f5ea43e889936a3709af68dfe3751881acefe4ecf0dbd30ba571258

Limitations and responsible use

The checkpoint was selected primarily on English narration and has not been validated equally across all languages or production workloads. It may inherit pronunciation, hallucination, pacing, and robustness limitations from the base model.

This is a research voice checkpoint. It is not affiliated with or endorsed by the source speaker. Do not use it for deceptive impersonation, fraud, harassment, or to imply endorsement. Users are responsible for obtaining any required consent and complying with applicable privacy, publicity, copyright, and disclosure requirements.

Base model

• Qwen3-TTS technical report
• Qwen3-TTS source repository