fish_speech/configs/modded_dac_vq.yaml

_target_: fish_speech.models.dac.modded_dac.DAC
# Model setup
sample_rate: 44100
encoder_dim: 64
encoder_rates: [2, 4, 8, 8]
decoder_dim: 1536
decoder_rates: [8, 8, 4, 2]
encoder_transformer_layers: [0, 0, 0, 4]
decoder_transformer_layers: [4, 0, 0, 0]
transformer_general_config:
  _target_: fish_speech.models.dac.modded_dac.ModelArgs
  _partial_: true
  block_size: 16384
  n_local_heads: -1
  head_dim: 64
  rope_base: 10000
  norm_eps: 1e-5
  dropout_rate: 0.1
  attn_dropout_rate: 0.1
  channels_first: true
# Quantization
quantizer:
  _target_: fish_speech.models.dac.rvq.DownsampleResidualVectorQuantize
  input_dim: 1024
  n_codebooks: 9
  codebook_size: 1024
  codebook_dim: 8
  quantizer_dropout: 0.5
  downsample_factor: [2, 2]
  post_module: &transformer_module
    _target_: fish_speech.models.dac.modded_dac.WindowLimitedTransformer
    causal: true
    window_size: 128  # empirically this does not seem to matter
    input_dim: 1024
    config: &transformer_config
      _target_: fish_speech.models.dac.modded_dac.ModelArgs
      block_size: 4096
      n_layer: 8
      n_head: 16
      dim: 1024
      intermediate_size: 3072
      n_local_heads: -1
      head_dim: 64
      rope_base: 10000
      norm_eps: 1e-5
      dropout_rate: 0.1
      attn_dropout_rate: 0.1
      channels_first: true
  pre_module: *transformer_module
  semantic_codebook_size: 4096