Any-to-Any
ESPnet
PyTorch
English
audio
multimodal
speech-language-model
audio-understanding
audio-generation
audio-to-text
text-to-audio
rich-caption
speech
music
environmental-sound
Instructions to use espnet/bagpiper with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ESPnet
How to use espnet/bagpiper with ESPnet:
unknown model type (must be text-to-speech or automatic-speech-recognition)
- Notebooks
- Google Colab
- Kaggle
Download config.yaml from espnet/bagpiper: direct link, hf CLI and curl.
- Browser
- Download file 2.02 kB
-
https://huggingface.co/espnet/bagpiper/resolve/main/config.yaml
- Command line
-
hf download hf://espnet/bagpiper/config.yaml
-
curl -L -o config.yaml https://huggingface.co/espnet/bagpiper/resolve/main/config.yaml
2.02 kB
| 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 | |