FunASR/egs_modelscope/common

ModelScope Model

How to finetune and infer using a pretrained ModelScope Model

Finetune

• Modify finetune training related parameters in conf/train_asr_paraformer_sanm_50e_16d_2048_512_lfr6.yaml
• Setting parameters in modelscope_common_finetune.sh
  • dataset: the dataset dir needs to include files: train/wav.scp, train/text; optional dev/wav.scp, dev/text, test/wav.scp test/text
  • tag: exp tag
  • init_model_name: speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch # pre-trained model, download from modelscope during fine-tuning

• Then you can run the pipeline to finetune with our model download from modelscope:

  sh ./modelscope_common_finetune.sh
  

Inference

Or you can use the finetuned model for inference directly.

• Setting parameters in modelscope_common_infer.sh
  • data_dir: # wav list, ${data_dir}/wav.scp
  • exp_dir: the result path
  • model_name: speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch # pre-trained model, download from modelscope

• Then you can run the pipeline to infer with:

  sh ./modelscope_common_infer.sh