{
  "model_type": "vui",
  "library_name": "vui",
  "pipeline_tag": "text-to-speech",
  "license": "apache-2.0",
  "language": [
    "en"
  ],
  "architectures": [
    "VuiForConditionalGeneration"
  ],
  "model_files": {
    "base": "vui-nano.safetensors",
    "tokenizer": "HuggingFaceTB/SmolLM2-135M"
  },
  "model_variants": {
    "vui-nano": {
      "description": "Small, context-aware streaming TTS trained on real conversations — Llama-style backbone with an RQ-Transformer acoustic head over the Qwen3-TTS codec. Conditions on dialogue history (text and prior-turn audio) across a ~6-minute context.",
      "file": "vui-nano.safetensors",
      "params": 305356033,
      "size_mb": 611,
      "active_params": 218623489
    }
  },
  "model_config": {
    "d_model": 768,
    "n_layers": 22,
    "n_heads": 8,
    "n_kv_heads": null,
    "bias": false,
    "use_rotary_emb": true,
    "rope_theta": 10000.0,
    "use_rq_transformer": true,
    "rq_n_layers": 5,
    "rq_d_model": 768,
    "rq_n_heads": 8,
    "codebook_size": 2048,
    "n_quantizers": 16,
    "codec_hz": 12.5,
    "spk_emb_dim": 1024,
    "max_text_tokens": 100,
    "max_audio_tokens": 100
  },
  "tokenizer_config": {
    "base_tokenizer": "HuggingFaceTB/SmolLM2-135M",
    "add_time_tokens": false
  },
  "audio_codec": {
    "name": "qwen3-tts",
    "native_sample_rate": 24000
  },
  "capabilities": [
    "text-to-speech",
    "conversational-speech",
    "context-aware",
    "voice-cloning",
    "streaming",
    "on-device-inference",
    "cpu-inference"
  ],
  "torch_dtype": "bfloat16",
  "framework": "pytorch",
  "sample_rate": 24000
}