{
 "architectures": [
  "HeartCodec"
 ],
 "attention_head_dim": 64,
 "causal": true,
 "codebook_dim": 32,
 "codebook_size": 8192,
 "commitment_weight": 1.0,
 "decay": 0.9,
 "default_kernel_size": 7,
 "delay_kernel_size": 5,
 "dim": 512,
 "downsample_factors": [
  3,
  4,
  4,
  4,
  5
 ],
 "downsample_kernel_sizes": [
  6,
  8,
  8,
  8,
  10
 ],
 "in_channels": 1024,
 "init_channel": 64,
 "latent_hidden_dim": 128,
 "model_type": "heartcodec",
 "norm_type": "ada_norm_single",
 "num_attention_heads": 24,
 "num_bands": 1,
 "num_layers": 24,
 "num_layers_2": 6,
 "num_quantizers": 8,
 "num_samples": 2,
 "out_channels": 256,
 "res_kernel_size": 7,
 "sample_rate": 48000,
 "threshold_ema_dead_code": 2,
 "torch_dtype": "float32",
 "transformers_version": "4.45.1",
 "upsample_factors": [
  5,
  4,
  4,
  4,
  3
 ],
 "upsample_kernel_sizes": [
  10,
  8,
  8,
  8,
  6
 ],
 "use_cosine_sim": false,
 "mlx_heartmula": {
  "component": "codec",
  "tier": "fp16",
  "source": {
   "repo": "HeartMuLa/HeartCodec-oss-20260123",
   "revision": "f889dab"
  },
  "oracle": "HeartMuLa/heartlib@5858ca8",
  "renames": [
   [
    "^scalar_model\\.decoder\\.0\\.",
    "scalar_model.pre_conv."
   ],
   [
    "^scalar_model\\.decoder\\.([1-5])\\.up_conv\\.layer\\.",
    "blocks.{N-1}\u2026"
   ],
   [
    "^scalar_model\\.decoder\\.([1-5])\\.convs\\.",
    "blocks.{N-1}\u2026"
   ],
   [
    "^scalar_model\\.decoder\\.6\\.",
    "scalar_model.post."
   ],
   [
    "^scalar_model\\.decoder\\.7\\.",
    "scalar_model.out_conv."
   ]
  ],
  "transforms": "decode path only (SQ-Codec encoder, RVQ EMA buffers, vq_embed.project_in dropped); weight_norm folded in fp32 with torch._weight_norm(v, g, 0); Conv1d (O,I,K)->(O,K,I); ConvTranspose1d (I,O,K)->(O,K,I); RVQ codebooks (1,8192,32)->(8192,32); SQ decoder list renamed; then .to(float16)",
  "tensors": 506
 }
}