from funasr import AutoModel # paraformer-zh is a multi-functional asr model # use vad, punc, spk or not as you need model = AutoModel(model="paraformer-zh", vad_model="fsmn-vad", punc_model="ct-punc", # spk_model="cam++", ) res = model.generate(input=f"{model.model_path}...
from funasr import AutoModel # paraformer-zh is a multi-functional asr model # use vad, punc, spk or not as you need model = AutoModel(model="paraformer-zh", vad_model="fsmn-vad", punc_model="ct-punc", # spk_model="cam++", ) res = model.generate(input=f"{model.model_path}...
Test ONNX # pip3 install -U funasr-onnx from funasr_onnx import Paraformer model_dir = "damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch" model = Paraformer(model_dir, batch_size=1, quantize=True) wav_path = ['~/.cache/modelscope/hub/damo/speech_paraformer...
Test ONNX # pip3 install -U funasr-onnx from funasr_onnx import Paraformer model_dir = "damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch" model = Paraformer(model_dir, batch_size=1, quantize=True) wav_path = ['~/.cache/modelscope/hub/damo/speech_paraformer...
from funasr import AutoModel # paraformer-zh is a multi-functional asr model # use vad, punc, spk or not as you need model = AutoModel(model="paraformer-zh", vad_model="fsmn-vad", punc_model="ct-punc", # spk_model="cam++", ) res = model.generate(input=f"{model.model_path}...
funasr ++model=paraformer-zh ++vad_model="fsmn-vad" ++punc_model="ct-punc" ++input=asr_example_zh.wav Notes: Support recognition of single audio file, as well as file list in Kaldi-style wav.scp format: wav_id wav_pat Speech Recognition (Non-streaming) SenseVoice from funasr import ...
Test ONNX# pip3 install -U funasr-onnx from funasr_onnx import Paraformer model_dir = "damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch" model = Paraformer(model_dir, batch_size=1, quantize=True) wav_path = ['~/.cache/modelscope/hub/damo/speech_paraformer-...
from funasr import AutoModel # paraformer-zh is a multi-functional asr model # use vad, punc, spk or not as you need model = AutoModel(model="paraformer-zh", vad_model="fsmn-vad", punc_model="ct-punc", # spk_model="cam++", ) res = model.generate(input=f"{model.model_path}...
onnxfromfunasr_onnximportParaformermodel_dir="damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch"model=Paraformer(model_dir,batch_size=1,quantize=True)wav_path=['~/.cache/modelscope/hub/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/example/...
Test ONNX # pip3 install -U funasr-onnx from funasr_onnx import Paraformer model_dir = "damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch" model = Paraformer(model_dir, batch_size=1, quantize=True) wav_path = ['~/.cache/modelscope/hub/damo/speech_paraformer...