许可证: mit
数据集:

• mozilla-foundation/common_voice_17_0
  语言:
• 俄语
  基础模型:
• openai/whisper-large-v3-turbo
  任务标签: 自动语音识别
  评估指标:
• 准确率
  库名称: transformers
  标签:
• 通话

该模型使用两块A100 40GB显卡、128GB内存及两颗至强48核2.4GHz处理器训练

• 耗时约7小时
• 训练数据集包含来自Mozilla Common Voice 17的11.8万条音频样本

使用示例

from transformers import pipeline  
import gradio as gr  
import time  

pipe = pipeline(  
    model="dvislobokov/whisper-large-v3-turbo-russian",  
    tokenizer="dvislobokov/whisper-large-v3-turbo-russian",  
    task='automatic-speech-recognition',  
    device='cpu'  
)  

def transcribe(audio):  
    start = time.time()  
    text = pipe(audio, return_timestamps=True)['text']  
    print(time.time() - start)  
    return text  

iface = gr.Interface(  
    fn=transcribe,  
    inputs=gr.Audio(sources=['microphone', 'upload'], type='filepath'),  
    outputs='text'  
)  

iface.launch(share=True)