{
  "architecture": "chatterbox",
  "model": "ResembleAI/chatterbox",
  "format": "litert",
  "variant": "fp16-multilingual",
  "deployment_complete": true,
  "voice": "default (zero-shot); cloning = follow-up (needs voice-encoder + s3-tokenizer + cond_enc graphs)",
  "sample_rate": 24000,
  "languages": [
    "ar",
    "da",
    "de",
    "el",
    "en",
    "es",
    "fi",
    "fr",
    "he",
    "hi",
    "it",
    "ja",
    "ko",
    "ms",
    "nl",
    "no",
    "pl",
    "pt",
    "ru",
    "sv",
    "sw",
    "tr",
    "zh"
  ],
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    "num_layers": 30,
    "num_kv_heads": 16,
    "head_dim": 64,
    "text_vocab": 2454,
    "speech_vocab": 8194,
    "start_speech_token": 6561,
    "stop_speech_token": 6562,
    "start_text_token": 255,
    "stop_text_token": 0,
    "cond_emb_len": 34,
    "prefill_text_pad": 478,
    "prefill_total": 512,
    "max_cache_tokens": 1536,
    "max_generated_tokens": 1000,
    "cfg_weight": 0.5,
    "temperature": 0.8,
    "batch": 1,
    "pipeline": "prefill(text_token_ids, cond_emb) -> cache; step(speech_token_id, speech_pos_idx, cache_position, cache) loop; BOS(6561) is step 0",
    "cache_layout": "per-layer key[1,16,cache_len,64] + value[1,16,cache_len,64]",
    "cfg_note": "batch=1; run cond + uncond (text_emb[1].zero_()) as two calls, combine: logits = cond + w*(cond-uncond)"
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    "estimator_max_frames": 1024,
    "inference_steps": 10,
    "solver": "euler",
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    "token_mel_ratio": 2,
    "prompt_feat_frames": 314
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    "shape": [
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    ]
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    "flow_encoder": "chatterbox-flow-encoder.tflite",
    "flow_estimator": "chatterbox-flow-estimator.tflite",
    "hift": "chatterbox-hift.tflite"
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    "t3_step": "fp16",
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  },
  "export": {
    "source_repo": "ResembleAI/chatterbox",
    "toolchain": "ai_edge_torch 0.6 + ai_edge_quantizer (dynamic_legacy_wi8_afp32 on T3)",
    "embeddings": "folded into T3 graphs (token-ID inputs); text/speech emb + learned pos inside graph",
    "kv_cache": "graph IO, functional StaticLayer.update; prefill cache=total, copy first prefix_len into step cache 1536",
    "stft": "iSTFT/STFT re-expressed as fixed-basis Conv1d/ConvTranspose1d",
    "flow_embeddings": "folded into flow_encoder_v2 (token-ID); input_embedding + encoder_proj inside graph",
    "t3_precision": "fp16 (float_casting); int8 too lossy for Arabic"
  },
  "flow_cond": {
    "voice": "default (zero-shot)",
    "spks": {
      "file": "spks.bin",
      "dtype": "float32",
      "shape": [
        1,
        80
      ]
    },
    "prompt_token": {
      "file": "prompt_token.bin",
      "dtype": "int32",
      "shape": [
        1,
        157
      ]
    },
    "prompt_feat": {
      "file": "prompt_feat.bin",
      "dtype": "float32",
      "shape": [
        1,
        314,
        80
      ]
    },
    "note": "host: full_token = prompt_token ++ speech_tokens; flow_encoder -> mu; 10x Euler CFM (estimator batch-2 CFG, dxdt=1.7*cond-0.7*uncond, t_span=1-cos(linspace(0,1,11)*pi/2)) with x init = randn; mel = x[:,:,prompt_feat_frames:]; hift -> 24k pcm"
  },
  "precision_note": "T3 graphs are fp16 (multilingual, incl. Arabic). int8 T3 is ~2x smaller but English-quality only (diverges on Arabic); available on request."
}