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README.md

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+---
+license: apache-2.0
+pipeline_tag: text-to-speech
+library_name: qwen-tts
+tags:
+- audio
+- tts
+- qwen
+- multilingual
+---
+
+# Qwen3-TTS
+
+<br>
+
+<p align="center">
+    <img src="https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen3-TTS-Repo/qwen3_tts_logo.png" width="400"/>
+<p>
+
+<p align="center">
+&nbsp&nbsp🤗 <a href="https://huggingface.co/collections/Qwen/qwen3-tts">Hugging Face</a>&nbsp&nbsp | &nbsp&nbsp🤖 <a href="https://modelscope.cn/collections/Qwen/Qwen3-TTS">ModelScope</a>&nbsp&nbsp | &nbsp&nbsp📑 <a href="https://qwen.ai/blog?id=qwen3tts-0115">Blog</a>&nbsp&nbsp | &nbsp&nbsp📑 <a href="https://huggingface.co/papers/2601.15621">Paper</a>&nbsp&nbsp | &nbsp&nbsp💻 <a href="https://github.com/QwenLM/Qwen3-TTS">GitHub</a>
+</p>
+
+We release **Qwen3-TTS**, a series of powerful speech generation models developed by Qwen, offering comprehensive support for voice cloning, voice design, ultra-high-quality human-like speech generation, and natural language-based voice control.
+
+## Overview
+Qwen3-TTS covers 10 major languages (Chinese, English, Japanese, Korean, German, French, Russian, Portuguese, Spanish, and Italian) as well as multiple dialectal voice profiles. Key features:
+
+* **Powerful Speech Representation**: Powered by the self-developed Qwen3-TTS-Tokenizer-12Hz, it achieves efficient acoustic compression and high-dimensional semantic modeling.
+* **Universal End-to-End Architecture**: Utilizing a discrete multi-codebook LM architecture to bypass traditional information bottlenecks.
+* **Extreme Low-Latency Streaming Generation**: Supports streaming generation with end-to-end synthesis latency as low as 97ms.
+* **Intelligent Voice Control**: Supports speech generation driven by natural language instructions for flexible control over timbre, emotion, and prosody.
+
+## Quickstart
+
+### Environment Setup
+
+Install the `qwen-tts` Python package from PyPI:
+
+```bash
+pip install -U qwen-tts
+```
+
+### Python Package Usage
+
+```python
+import torch
+import soundfile as sf
+from qwen_tts import Qwen3TTSModel
+
+# Load the model
+model = Qwen3TTSModel.from_pretrained(
+    "Qwen/Qwen3-TTS-12Hz-1.7B-CustomVoice",
+    device_map="cuda:0",
+    dtype=torch.bfloat16,
+    attn_implementation="flash_attention_2",
+)
+
+# Custom Voice Generation
+wavs, sr = model.generate_custom_voice(
+    text="其实我真的有发现，我是一个特别善于观察别人情绪的人。",
+    language="Chinese",
+    speaker="Vivian",
+    instruct="用特别愤怒的语气说",
+)
+sf.write("output.wav", wavs[0], sr)
+```
+
+## Evaluation
+
+Zero-shot speech generation on the Seed-TTS test set (Word Error Rate (WER, ↓)):
+
+| Model | test-zh | test-en |
+|---|---|---|
+| Qwen3-TTS-12Hz-1.7B-Base | 0.77 | 1.24 |
+
+## Citation
+
+If you find our paper and code useful in your research, please consider giving a star ⭐ and citation 📝:
+
+```BibTeX
+@article{Qwen3-TTS,
+  title={Qwen3-TTS Technical Report},
+  author={Hangrui Hu and Xinfa Zhu and Ting He and Dake Guo and Bin Zhang and Xiong Wang and Zhifang Guo and Ziyue Jiang and Hongkun Hao and Zishan Guo and Xinyu Zhang and Pei Zhang and Baosong Yang and Jin Xu and Jingren Zhou and Junyang Lin},
+  journal={arXiv preprint arXiv:2601.15621},
+  year={2026}
+}
+```

chute_config.yml

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+# Image + node + Chute for Vocence deploy. Required in the HF repo at build fred time.
+
+Image:
+  from_base: parachutes/python:3.12
+  run_command:
+    - pip install torch torchaudio transformers accelerate huggingface_hub pyyaml soundfile librosa
+    - pip install -U qwen-tts
+  set_workdir: /app
+
+NodeSelector:
+  gpu_count: 1
+  min_vram_gb_per_gpu: 24
+  include: ["pro_6000"]
+  exclude: []
+
+Chute:
+  tagline: Vocence TTS — Qwen3 PromptTTS (weights in repo)
+  readme: Qwen3 12Hz TTS snapshot + miner.py for Vocence
+  shutdown_after_seconds: 86400
+  concurrency: 1
+  max_instances: 1
+  scaling_threshold: 0.5
+  tee: true

config.json

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+{
+  "architectures": [
+    "Qwen3TTSForConditionalGeneration"
+  ],
+  "assistant_token_id": 77091,
+  "im_end_token_id": 151645,
+  "im_start_token_id": 151644,
+  "tts_bos_token_id": 151672,
+  "tts_eos_token_id": 151673,
+  "tts_pad_token_id": 151671,
+  "model_type": "qwen3_tts",
+  "tokenizer_type": "qwen3_tts_tokenizer_12hz",
+  "tts_model_size": "1b7",
+  "tts_model_type": "voice_design",
+  "talker_config": {
+    "attention_bias": false,
+    "attention_dropout": 0,
+    "code_predictor_config": {
+      "_name_or_path": "",
+      "add_cross_attention": false,
+      "architectures": null,
+      "attention_bias": false,
+      "attention_dropout": 0,
+      "bad_words_ids": null,
+      "begin_suppress_tokens": null,
+      "bos_token_id": null,
+      "chunk_size_feed_forward": 0,
+      "cross_attention_hidden_size": null,
+      "decoder_start_token_id": null,
+      "diversity_penalty": 0.0,
+      "do_sample": false,
+      "early_stopping": false,
+      "encoder_no_repeat_ngram_size": 0,
+      "eos_token_id": null,
+      "exponential_decay_length_penalty": null,
+      "finetuning_task": null,
+      "forced_bos_token_id": null,
+      "forced_eos_token_id": null,
+      "head_dim": 128,
+      "hidden_act": "silu",
+      "hidden_size": 1024,
+      "id2label": {
+        "0": "LABEL_0",
+        "1": "LABEL_1"
+      },
+      "initializer_range": 0.02,
+      "intermediate_size": 3072,
+      "is_decoder": false,
+      "is_encoder_decoder": false,
+      "label2id": {
+        "LABEL_0": 0,
+        "LABEL_1": 1
+      },
+      "layer_types": [
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention"
+      ],
+      "length_penalty": 1.0,
+      "max_length": 20,
+      "max_position_embeddings": 65536,
+      "max_window_layers": 28,
+      "min_length": 0,
+      "model_type": "qwen3_tts_talker_code_predictor",
+      "no_repeat_ngram_size": 0,
+      "num_attention_heads": 16,
+      "num_beam_groups": 1,
+      "num_beams": 1,
+      "num_code_groups": 16,
+      "num_hidden_layers": 5,
+      "num_key_value_heads": 8,
+      "num_return_sequences": 1,
+      "output_attentions": false,
+      "output_hidden_states": false,
+      "output_scores": false,
+      "pad_token_id": null,
+      "prefix": null,
+      "problem_type": null,
+      "pruned_heads": {},
+      "remove_invalid_values": false,
+      "repetition_penalty": 1.0,
+      "return_dict": true,
+      "return_dict_in_generate": false,
+      "rms_norm_eps": 1e-06,
+      "rope_scaling": null,
+      "rope_theta": 1000000,
+      "sep_token_id": null,
+      "sliding_window": null,
+      "suppress_tokens": null,
+      "task_specific_params": null,
+      "temperature": 1.0,
+      "tf_legacy_loss": false,
+      "tie_encoder_decoder": false,
+      "tie_word_embeddings": false,
+      "tokenizer_class": null,
+      "top_k": 50,
+      "top_p": 1.0,
+      "dtype": null,
+      "torchscript": false,
+      "typical_p": 1.0,
+      "use_bfloat16": false,
+      "use_cache": true,
+      "use_sliding_window": false,
+      "vocab_size": 2048
+    },
+    "codec_bos_id": 2149,
+    "codec_eos_token_id": 2150,
+    "codec_think_id": 2154,
+    "codec_language_id": {
+      "chinese": 2055,
+      "english": 2050,
+      "german": 2053,
+      "italian": 2070,
+      "portuguese": 2071,
+      "spanish": 2054,
+      "japanese": 2058,
+      "korean": 2064,
+      "french": 2061,
+      "russian": 2069
+    },
+    "codec_nothink_id": 2155,
+    "codec_pad_id": 2148,
+    "codec_think_bos_id": 2156,
+    "codec_think_eos_id": 2157,
+    "spk_id": {
+      "data": 3000
+    },
+    "spk_is_dialect": {
+      "data": false
+    },
+    "head_dim": 128,
+    "hidden_act": "silu",
+    "hidden_size": 2048,
+    "initializer_range": 0.02,
+    "intermediate_size": 6144,
+    "max_position_embeddings": 32768,
+    "model_type": "qwen3_tts_talker",
+    "num_attention_heads": 16,
+    "num_code_groups": 16,
+    "num_hidden_layers": 28,
+    "num_key_value_heads": 8,
+    "position_id_per_seconds": 13,
+    "rms_norm_eps": 1e-06,
+    "rope_scaling": {
+      "interleaved": true,
+      "mrope_section": [
+        24,
+        20,
+        20
+      ],
+      "rope_type": "default",
+      "type": "default"
+    },
+    "rope_theta": 1000000,
+    "sliding_window": null,
+    "text_hidden_size": 2048,
+    "text_vocab_size": 151936,
+    "use_cache": true,
+    "use_sliding_window": false,
+    "vocab_size": 3072
+  },
+  "transformers_version": "4.57.3"
+}

generation_config.json

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+{
+  "do_sample": true,
+  "repetition_penalty": 1.05,
+  "temperature": 0.9,
+  "top_p": 1.0,
+  "top_k": 50,
+  "subtalker_dosample": true,
+  "subtalker_temperature": 0.9,
+  "subtalker_top_p": 1.0,
+  "subtalker_top_k": 50,
+  "max_new_tokens": 8192
+}

miner.py

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+from __future__ import annotations
+
+from concurrent.futures import ThreadPoolExecutor, TimeoutError as FutureTimeout
+from pathlib import Path
+from typing import Any
+
+import numpy as np
+
+
+VOCENCE_CONFIG = "vocence_config.yaml"
+QWEN_ANCHOR = "config.json"
+WARMUP_SECONDS = 180.0
+
+
+def _load_yaml(path: Path) -> dict[str, Any]:
+    if not path.is_file():
+        return {}
+    from yaml import safe_load
+    with path.open("r", encoding="utf-8") as fh:
+        return safe_load(fh) or {}
+
+
+def _select_device(prefer_cuda: bool):
+    import torch
+    has_cuda = torch.cuda.is_available()
+    device = "cuda:0" if (prefer_cuda and has_cuda) else "cpu"
+    return device, torch, has_cuda
+
+
+def _select_dtype(torch_mod, want_bf16: bool, has_cuda: bool):
+    return torch_mod.bfloat16 if (want_bf16 and has_cuda) else torch_mod.float32
+
+
+def _build_qwen(snapshot: Path, device: str, dtype: Any, attn: str):
+    from qwen_tts import Qwen3TTSModel
+    return Qwen3TTSModel.from_pretrained(
+        pretrained_model_name_or_path=str(snapshot),
+        device_map=device,
+        dtype=dtype,
+        attn_implementation=attn,
+    )
+
+
+def _attn_order(prefer_flash: bool) -> tuple[str, ...]:
+    return ("flash_attention_2", "sdpa") if prefer_flash else ("sdpa",)
+
+
+def _mono_pcm(arr: Any) -> np.ndarray:
+    wave = np.asarray(arr, dtype=np.float32)
+    return wave.mean(axis=1) if wave.ndim > 1 else wave
+
+
+def _settings(snapshot: Path) -> dict[str, Any]:
+    raw = _load_yaml(snapshot / VOCENCE_CONFIG)
+    rt = raw.get("runtime") or {}
+    gen = raw.get("generation") or {}
+    lim = raw.get("limits") or {}
+    return {
+        "language": str(lim.get("default_language") or rt.get("default_language") or "English"),
+        "sample_rate": int(gen.get("sample_rate", 24000)),
+        "cap_instruct": int(lim.get("max_instruction_chars", 600)),
+        "cap_text": int(lim.get("max_text_chars", 2000)),
+        "prefer_cuda": str(rt.get("device_preference", "cuda")).lower() == "cuda",
+        "prefer_bf16": str(rt.get("dtype", "bfloat16")).lower() == "bfloat16",
+        "prefer_flash": bool(rt.get("use_flash_attention_2", False)),
+    }
+
+
+class Miner:
+
+    def __init__(self, path_hf_repo: Path) -> None:
+        snapshot = Path(path_hf_repo).resolve()
+        if not (snapshot / QWEN_ANCHOR).is_file():
+            raise FileNotFoundError(f"snapshot missing {QWEN_ANCHOR}: {snapshot}")
+        self.snapshot = snapshot
+        self.cfg = _settings(snapshot)
+
+        device, torch_mod, has_cuda = _select_device(self.cfg["prefer_cuda"])
+        dtype = _select_dtype(torch_mod, self.cfg["prefer_bf16"], has_cuda)
+
+        last_err: BaseException | None = None
+        engine = None
+        for attn in _attn_order(self.cfg["prefer_flash"]):
+            try:
+                engine = _build_qwen(snapshot, device, dtype, attn)
+                tag = "bf16" if self.cfg["prefer_bf16"] and has_cuda else "fp32"
+                print(f"[Miner] qwen3-tts ready: device={device} dtype={tag} attn={attn}")
+                break
+            except Exception as exc:
+                last_err = exc
+        if engine is None:
+            raise RuntimeError(f"qwen3-tts load failed: {last_err!r}")
+        self.engine = engine
+
+    def __repr__(self) -> str:
+        return f"<Miner snapshot={self.snapshot.name} lang={self.cfg['language']!r}>"
+
+    def warmup(self) -> None:
+        with ThreadPoolExecutor(max_workers=1) as pool:
+            future = pool.submit(self.generate_wav, "Neutral voice.", "Warmup phrase.")
+            try:
+                future.result(timeout=WARMUP_SECONDS)
+            except FutureTimeout:
+                raise RuntimeError(f"Miner warmup exceeded {WARMUP_SECONDS}s")
+
+    def generate_wav(self, instruction: str, text: str) -> tuple[np.ndarray, int]:
+        cap_i = self.cfg["cap_instruct"]
+        cap_t = self.cfg["cap_text"]
+        prompt = instruction[:cap_i] if cap_i > 0 else instruction
+        body = text[:cap_t] if cap_t > 0 else text
+        wavs, sr = self.engine.generate_voice_design(
+            text=body,
+            instruct=prompt,
+            language=self.cfg["language"],
+        )
+        if not wavs or wavs[0] is None:
+            raise ValueError("qwen3-tts returned no audio")
+        return _mono_pcm(wavs[0]), int(sr)

model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:b5ce24aab3afac1df69bc2b2807140ff90a082d98782c3d3126ab3a4ed5bc888
+size 3833402520

preprocessor_config.json

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+{
+  "padding_side": "left",
+  "padding_value": 0.0,
+  "processor_class": "Qwen3TTSProcessor",
+  "return_attention_mask": true
+}

speech_tokenizer/config.json

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+{
+  "architectures": [
+    "Qwen3TTSTokenizerV2Model"
+  ],
+  "model_type": "qwen3_tts_tokenizer_12hz",
+  "encoder_valid_num_quantizers": 16,
+  "input_sample_rate": 24000,
+  "output_sample_rate": 24000,
+  "decode_upsample_rate": 1920,
+  "encode_downsample_rate": 1920,
+  "decoder_config": {
+    "attention_bias": false,
+    "attention_dropout": 0.0,
+    "latent_dim": 1024,
+    "codebook_dim": 512,
+    "codebook_size": 2048,
+    "decoder_dim": 1536,
+    "hidden_act": "silu",
+    "hidden_size": 512,
+    "intermediate_size": 1024,
+    "layer_scale_initial_scale": 0.01,
+    "max_position_embeddings": 8000,
+    "head_dim": 64,
+    "num_attention_heads": 16,
+    "num_hidden_layers": 8,
+    "num_key_value_heads": 16,
+    "num_quantizers": 16,
+    "num_semantic_quantizers": 1,
+    "rms_norm_eps": 1e-05,
+    "rope_theta": 10000,
+    "semantic_codebook_size": 4096,
+    "sliding_window": 72,
+    "upsample_rates": [
+      8,
+      5,
+      4,
+      3
+    ],
+    "upsampling_ratios": [
+      2,
+      2
+    ],
+    "vector_quantization_hidden_dimension": 512
+  },
+  "encoder_config": {
+    "_frame_rate": 12.5,
+    "attention_bias": false,
+    "attention_dropout": 0.0,
+    "audio_channels": 1,
+    "codebook_dim": 256,
+    "codebook_size": 2048,
+    "compress": 2,
+    "dilation_growth_rate": 2,
+    "dtype": "float32",
+    "head_dim": 64,
+    "hidden_act": "gelu",
+    "hidden_size": 512,
+    "initializer_range": 0.02,
+    "intermediate_size": 2048,
+    "kernel_size": 7,
+    "last_kernel_size": 3,
+    "layer_scale_initial_scale": 0.01,
+    "max_position_embeddings": 8000,
+    "norm_eps": 1e-05,
+    "normalize": false,
+    "num_attention_heads": 8,
+    "num_filters": 64,
+    "num_hidden_layers": 8,
+    "num_key_value_heads": 8,
+    "num_quantizers": 32,
+    "num_residual_layers": 1,
+    "num_semantic_quantizers": 1,
+    "pad_mode": "constant",
+    "residual_kernel_size": 3,
+    "rope_theta": 10000.0,
+    "sampling_rate": 24000,
+    "sliding_window": 250,
+    "transformers_version": "4.57.0.dev0",
+    "trim_right_ratio": 1.0,
+    "upsample_groups": 512,
+    "upsampling_ratios": [
+      8,
+      6,
+      5,
+      4
+    ],
+    "use_cache": false,
+    "use_causal_conv": true,
+    "use_conv_shortcut": false,
+    "use_streaming": false,
+    "vector_quantization_hidden_dimension": 256
+  },
+  "transformers_version": "4.57.3"
+}

speech_tokenizer/configuration.json

@@ -0,0 +1 @@
+{"framework": "pytorch", "task": "feature-extraction", "allow_remote": true}

speech_tokenizer/model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:836b7b357f5ea43e889936a3709af68dfe3751881acefe4ecf0dbd30ba571258
+size 682293092

speech_tokenizer/preprocessor_config.json

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+{
+  "chunk_length_s": null,
+  "feature_extractor_type": "EncodecFeatureExtractor",
+  "feature_size": 1,
+  "overlap": null,
+  "padding_side": "right",
+  "padding_value": 0.0,
+  "return_attention_mask": true,
+  "sampling_rate": 24000
+}

tokenizer_config.json

@@ -0,0 +1,316 @@
+{
+  "add_bos_token": false,
+  "add_prefix_space": false,
+  "added_tokens_decoder": {
+    "151643": {
+      "content": "<|endoftext|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151644": {
+      "content": "<|im_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151645": {
+      "content": "<|im_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151646": {
+      "content": "<|object_ref_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151647": {
+      "content": "<|object_ref_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151648": {
+      "content": "<|box_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151649": {
+      "content": "<|box_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151650": {
+      "content": "<|quad_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151651": {
+      "content": "<|quad_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151652": {
+      "content": "<|vision_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151653": {
+      "content": "<|vision_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151654": {
+      "content": "<|vision_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151655": {
+      "content": "<|image_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151656": {
+      "content": "<|video_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151657": {
+      "content": "<tool_call>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151658": {
+      "content": "</tool_call>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151659": {
+      "content": "<|fim_prefix|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151660": {
+      "content": "<|fim_middle|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151661": {
+      "content": "<|fim_suffix|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151662": {
+      "content": "<|fim_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151663": {
+      "content": "<|repo_name|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151664": {
+      "content": "<|file_sep|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151665": {
+      "content": "<tool_response>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151666": {
+      "content": "</tool_response>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151667": {
+      "content": "<think>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151668": {
+      "content": "</think>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151669": {
+      "content": "<|audio_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151670": {
+      "content": "<|audio_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151671": {
+      "content": "<tts_pad>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151672": {
+      "content": "<tts_text_bos>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151673": {
+      "content": "<tts_text_eod>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151674": {
+      "content": "<tts_text_bos_single>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151675": {
+      "content": "<|audio_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "additional_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>",
+    "<|object_ref_start|>",
+    "<|object_ref_end|>",
+    "<|box_start|>",
+    "<|box_end|>",
+    "<|quad_start|>",
+    "<|quad_end|>",
+    "<|vision_start|>",
+    "<|vision_end|>",
+    "<|vision_pad|>",
+    "<|image_pad|>",
+    "<|video_pad|>",
+    "<|audio_start|>",
+    "<|audio_end|>",
+    "<tts_pad>",
+    "<tts_text_bos>",
+    "<tts_text_bos_single>",
+    "<|audio_pad|>"
+  ],
+  "extra_special_tokens": {
+    "image_token": "<|image_pad|>",
+    "audio_token": "<|audio_pad|>",
+    "video_token": "<|video_pad|>",
+    "vision_bos_token": "<|vision_start|>",
+    "vision_eos_token": "<|vision_end|>",
+    "audio_bos_token": "<|audio_start|>",
+    "audio_eos_token": "<|audio_end|>"
+  },
+  "bos_token": null,
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "model_max_length": 131072,
+  "pad_token": "<|endoftext|>",
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "unk_token": null,
+  "image_token": "<|image_pad|>",
+  "audio_token": "<|audio_pad|>",
+  "video_token": "<|video_pad|>",
+  "vision_bos_token": "<|vision_start|>",
+  "vision_eos_token": "<|vision_end|>",
+  "audio_bos_token": "<|audio_start|>",
+  "audio_eos_token": "<|audio_end|>"
+}

vocence_config.yaml

@@ -0,0 +1,16 @@
+# Miner + /health metadata. Weights live in this HF repo (no runtime model_id).
+runtime:
+  adapter: "qwen3_tts_repo_snapshot"
+  device_preference: "cuda"
+  dtype: "bfloat16"
+  default_language: "English"
+  use_flash_attention_2: false
+
+generation:
+  sample_rate: 24000
+  max_seconds: 30
+
+limits:
+  max_text_chars: 2000
+  max_instruction_chars: 600
+  default_language: "English"