mirror of
https://github.com/modelscope/FunASR
synced 2025-09-15 14:48:36 +08:00
1.8 KiB
1.8 KiB
Environments
torch >= 1.11.0
modelscope >= 1.2.0
Install modelscope and funasr
The installation is the same as funasr
Export model
Tips: torch>=1.11.0
python -m funasr.export.export_model \
--model-name [model_name] \
--export-dir [export_dir] \
--type [onnx, torch] \
--quantize \
--fallback-num [fallback_num]
model-name: the model is to export. It could be the models from modelscope, or local finetuned model(named: model.pb).
export-dir: the dir where the onnx is export.
type: onnx or torch, export onnx format model or torchscript format model.
quantize: true, export quantized model at the same time; false, export fp32 model only.
fallback-num: specify the number of fallback layers to perform automatic mixed precision quantization.
For example
Export onnx format model
Export model from modelscope
python -m funasr.export.export_model --model-name damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch --export-dir ./export --type onnx
Export model from local path, the model'name must be model.pb.
python -m funasr.export.export_model --model-name /mnt/workspace/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch --export-dir ./export --type onnx
Export torchscripts format model
Export model from modelscope
python -m funasr.export.export_model --model-name damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch --export-dir ./export --type torch
Export model from local path, the model'name must be model.pb.
python -m funasr.export.export_model --model-name /mnt/workspace/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch --export-dir ./export --type torch