bagpiper / config.yaml
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Add standard ESPnet configuration for download counting
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job_type: speechlm
# Reconstructed config that reproduces the model behind the public
# stage-2 pretrained BASE checkpoint (exp/opuslm_v2_stage2_pretrain_base,
# step 260000). The original launch script referenced this filename but it
# was never committed; recreated here as the base-tokenizer analog of
# conf/train_stage2_qwen3.yaml (Qwen3-8B-Base backbone/tokenizer).
# Vocab check: 256 special + 151936 (Qwen3-8B-Base) + 8200 (Xcodec 8x1025)
# = 160392 = embed_tokens rows in the checkpoint.
multimodal_io:
text:
tokenizer_name: Qwen/Qwen3-8B-Base
discrete_audio:
codec_choice: Xcodec
codec_hf_model_tag: hf-audio/xcodec-hubert-general
ssl_choice: null
ssl_hf_model_tag: null
delay_interleave: true
stream_weights: [0.125, 0.125, 0.125, 0.125, 0.125, 0.125, 0.125, 0.125]
continuous_audio:
encoder_choice: huggingface
encoder_hf_model_tag: Qwen/Qwen3-Omni-30B-A3B-Instruct
attn_implementation: flash_attention_3
dtype: bfloat16
model:
model_choice: parallel
model_hf_tag: Qwen/Qwen3-8B-Base
model_conf:
attn_implementation: flash_attention_3
dtype: bfloat16
# NOTE: compile_transformer_body / freeze_text_embeddings appear in the
# original stage configs but are dead keys in the current espnet2/speechlm
# code (referenced nowhere). transformers 5.x silently drops them; 4.57.x
# forwards them into the HF constructor and crashes. Omitted here.
activation_checkpointing: true
preprocessor:
audio_input: continuous_audio
audio_output: discrete_audio
loss_region: assistant
audio_cfg: 0.05
data_loading:
batchfy_method: pack
batch_size: 15000
save_loader_state: false
seed: 43
num_workers: 6
trainer:
deepspeed_config: conf/deepspeed_stage2.json
freeze_param: [multimodal_io_dict.discrete_audio, multimodal_io_dict.continuous_audio]
max_step: 700000
save_interval: 5000
log_interval: 1