适配funasr1.0的modelscope版本（1.11.1）已经发布，如果需要使用pipeline进行推理，请更新版本：

pip install -U modelscope>=1.11.1 funasr>=1.0.2

用法已经更新至模型描述文档model card，举例：

from modelscope.pipelines import pipeline
from modelscope.utils.constant import Tasks

inference_pipeline = pipeline(
task=Tasks.auto_speech_recognition,
model='iic/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch', model_revision="v2.0.4",
vad_model='iic/speech_fsmn_vad_zh-cn-16k-common-pytorch', vad_model_revision="v2.0.4",
punc_model='iic/punc_ct-transformer_zh-cn-common-vocab272727-pytorch', punc_model_revision="v2.0.4",
)

rec_result = inference_pipeline('https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_zh.wav')
print(rec_result)

用法与funasr用法保存一致：

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", model_revision="v2.0.4",
vad_model="fsmn-vad", vad_model_revision="v2.0.4",
punc_model="ct-punc-c", punc_model_revision="v2.0.4",

              # spk_model="cam++", spk_model_revision="v2.0.2",
              )

res = model.generate(input=f"{model.model_path}/example/asr_example.wav",
batch_size_s=300,
hotword='魔搭')
print(res) 此回答整理自钉群“modelscope-funasr社区交流”