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update 8k uniasr recipe

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仁迷 2023-02-07 10:50:15 +08:00
parent c5f132a451
commit 6cc96a10eb
6 changed files with 6 additions and 6 deletions
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2
egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-zh-cn-8k-common-vocab3445-pytorch-offline/finetune.py
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@ -25,7 +25,7 @@ def modelscope_finetune(params):
if __name__ == '__main__': if __name__ == '__main__':
params = modelscope_args(model="damo/speech_UniASR_asr_2pass-zh-cn-8k-common-vocab3445-pytorch-online", data_path="./data") params = modelscope_args(model="damo/speech_UniASR_asr_2pass-zh-cn-8k-common-vocab3445-pytorch-offline", data_path="./data")
params.output_dir = "./checkpoint" # m模型保存路径 params.output_dir = "./checkpoint" # m模型保存路径
params.data_path = "./example_data/" # 数据路径 params.data_path = "./example_data/" # 数据路径
params.dataset_type = "small" # 小数据量设置small，若数据量大于1000小时，请使用large params.dataset_type = "small" # 小数据量设置small，若数据量大于1000小时，请使用large

2
egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-zh-cn-8k-common-vocab3445-pytorch-offline/infer.py
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@ -18,7 +18,7 @@ def modelscope_infer_core(output_dir, split_dir, njob, idx):
os.environ['CUDA_VISIBLE_DEVICES'] = str(gpu_id) os.environ['CUDA_VISIBLE_DEVICES'] = str(gpu_id)
inference_pipline = pipeline( inference_pipline = pipeline(
task=Tasks.auto_speech_recognition, task=Tasks.auto_speech_recognition,
model="damo/speech_UniASR_asr_2pass-zh-cn-8k-common-vocab3445-pytorch-online", model="damo/speech_UniASR_asr_2pass-zh-cn-8k-common-vocab3445-pytorch-offline",
output_dir=output_dir_job, output_dir=output_dir_job,
batch_size=1 batch_size=1
) )

2
egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-zh-cn-8k-common-vocab3445-pytorch-offline/infer_after_finetune.py
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@ -45,7 +45,7 @@ def modelscope_infer_after_finetune(params):
if __name__ == '__main__': if __name__ == '__main__':
params = {} params = {}
params["modelscope_model_name"] = "damo/speech_UniASR_asr_2pass-zh-cn-8k-common-vocab3445-pytorch-online" params["modelscope_model_name"] = "damo/speech_UniASR_asr_2pass-zh-cn-8k-common-vocab3445-pytorch-offline"
params["required_files"] = ["am.mvn", "decoding.yaml", "configuration.json"] params["required_files"] = ["am.mvn", "decoding.yaml", "configuration.json"]
params["output_dir"] = "./checkpoint" params["output_dir"] = "./checkpoint"
params["data_dir"] = "./data/test" params["data_dir"] = "./data/test"

2
egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-zh-cn-8k-common-vocab3445-pytorch-online/finetune.py
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@ -25,7 +25,7 @@ def modelscope_finetune(params):
if __name__ == '__main__': if __name__ == '__main__':
params = modelscope_args(model="damo/speech_UniASR_asr_2pass-zh-cn-8k-common-vocab3445-pytorch-offline", data_path="./data") params = modelscope_args(model="damo/speech_UniASR_asr_2pass-zh-cn-8k-common-vocab3445-pytorch-online", data_path="./data")
params.output_dir = "./checkpoint" # m模型保存路径 params.output_dir = "./checkpoint" # m模型保存路径
params.data_path = "./example_data/" # 数据路径 params.data_path = "./example_data/" # 数据路径
params.dataset_type = "small" # 小数据量设置small，若数据量大于1000小时，请使用large params.dataset_type = "small" # 小数据量设置small，若数据量大于1000小时，请使用large

2
egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-zh-cn-8k-common-vocab3445-pytorch-online/infer.py
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@ -18,7 +18,7 @@ def modelscope_infer_core(output_dir, split_dir, njob, idx):
os.environ['CUDA_VISIBLE_DEVICES'] = str(gpu_id) os.environ['CUDA_VISIBLE_DEVICES'] = str(gpu_id)
inference_pipline = pipeline( inference_pipline = pipeline(
task=Tasks.auto_speech_recognition, task=Tasks.auto_speech_recognition,
model="damo/speech_UniASR_asr_2pass-zh-cn-8k-common-vocab3445-pytorch-offline", model="damo/speech_UniASR_asr_2pass-zh-cn-8k-common-vocab3445-pytorch-online",
output_dir=output_dir_job, output_dir=output_dir_job,
batch_size=1 batch_size=1
) )

2
egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-zh-cn-8k-common-vocab3445-pytorch-online/infer_after_finetune.py
View File

@ -45,7 +45,7 @@ def modelscope_infer_after_finetune(params):
if __name__ == '__main__': if __name__ == '__main__':
params = {} params = {}
params["modelscope_model_name"] = "damo/speech_UniASR_asr_2pass-zh-cn-8k-common-vocab3445-pytorch-offline" params["modelscope_model_name"] = "damo/speech_UniASR_asr_2pass-zh-cn-8k-common-vocab3445-pytorch-online"
params["required_files"] = ["am.mvn", "decoding.yaml", "configuration.json"] params["required_files"] = ["am.mvn", "decoding.yaml", "configuration.json"]
params["output_dir"] = "./checkpoint" params["output_dir"] = "./checkpoint"
params["data_dir"] = "./data/test" params["data_dir"] = "./data/test"