content: [model]
  package = "bonito.crf"
  type = "seqdistmodel"
  
  [scaling]
  strategy = "pa"
  
  [run_info]
  sample_type = "dna"
  sample_rate = 5000
  
  [basecaller]
  chunksize = 12288
  overlap = 600
  
  [standardisation]
  standardise = 1
  mean = 93.69239463939118
  stdev = 23.506745239082388
  
  [qscore]
  scale = 1.05
  bias = 1.3
  
  [training_dataset]
  hash = "00fbcdaa1c39a77b216eafe93127dfab5bd77e6f855672cc8047a4977c78eb1c"
  
  [model.seqdist]
  state_len = 5
  alphabet = [ "N", "A", "C", "G", "T",]
  
  [model.encoder]
  type = "namedserial"
  
  [model.encoder.conv]
  type = "serial"
  [[model.encoder.conv.sublayers]]
  type = "convolution"
  insize = 1
  size = 64
  bias = true
  winlen = 5
  stride = 1
  padding = 2
  activation = "swish"
  norm = "batchnorm"
  
  [[model.encoder.conv.sublayers]]
  type = "convolution"
  insize = 64
  size = 64
  bias = true
  winlen = 5
  stride = 1
  padding = 2
  activation = "swish"
  norm = "batchnorm"
  
  [[model.encoder.conv.sublayers]]
  type = "convolution"
  insize = 64
  size = 128
  bias = true
  winlen = 9
  stride = 3
  padding = 4
  activation = "swish"
  norm = "batchnorm"
  
  [[model.encoder.conv.sublayers]]
  type = "convolution"
  insize = 128
  size = 128
  bias = true
  winlen = 9
  stride = 2
  padding = 4
  activation = "swish"
  norm = "batchnorm"
  
  [[model.encoder.conv.sublayers]]
  type = "convolution"
  insize = 128
  size = 512
  bias = true
  winlen = 5
  stride = 2
  padding = 2
  activation = "swish"
  norm = "batchnorm"
  
  [[model.encoder.conv.sublayers]]
  type = "permute"
  dims = [ 0, 2, 1,]
  
  [model.encoder.transformer_encoder]
  type = "stack"
  depth = 18
  
  [model.encoder.upsample]
  type = "linearupsample"
  d_model = 512
  scale_factor = 2
  
  [model.encoder.crf]
  type = "linearcrfencoder"
  insize = 512
  n_base = 4
  state_len = 5
  bias = false
  scale = 5.0
  blank_score = 2.0
  expand_blanks = true
  permute = [ 1, 0, 2,]
  
  [model.encoder.transformer_encoder.layer]
  type = "transformerencoderlayer"
  d_model = 512
  nhead = 8
  dim_feedforward = 2048
  deepnorm_alpha = 2.4494897
  deepnorm_beta = 0.2886751
  attn_window = [ 127, 128,]
  