| model_class: rnnt |
| sample_rate: 16000 |
| preprocessor: |
| _target_: gigaam.preprocess.FeatureExtractor |
| sample_rate: 16000 |
| features: 64 |
| win_length: 320 |
| hop_length: 160 |
| mel_scale: htk |
| n_fft: 320 |
| mel_norm: null |
| center: false |
| encoder: |
| _target_: gigaam.encoder.ConformerEncoder |
| feat_in: 64 |
| n_layers: 16 |
| d_model: 768 |
| subsampling_factor: 4 |
| ff_expansion_factor: 4 |
| self_attention_model: rotary |
| pos_emb_max_len: 5000 |
| n_heads: 16 |
| conv_kernel_size: 5 |
| flash_attn: false |
| subs_kernel_size: 5 |
| subsampling: conv1d |
| conv_norm_type: layer_norm |
| head: |
| _target_: gigaam.decoder.RNNTHead |
| decoder: |
| pred_hidden: 320 |
| pred_rnn_layers: 1 |
| num_classes: 1025 |
| joint: |
| enc_hidden: 768 |
| pred_hidden: 320 |
| joint_hidden: 320 |
| num_classes: 1025 |
| decoding: |
| _target_: gigaam.decoding.RNNTGreedyDecoding |
| vocabulary: null |
| model_path: /models/v3_e2e_rnnt_tokenizer.model |
| model_name: v3_e2e_rnnt |
| hashes: |
| model: 72e2a9b5c7caad963b2bbfd2f298c252 |
| tokenizer: 3b3bf8370e882885d79731592fc99f98 |
|
|
