| 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'] | |
| spent_time = (time.time() - start) | |
| return f'Spent time: {spent_time}\nText: {text}' | |
| iface = gr.Interface( | |
| fn=transcribe, | |
| inputs=gr.Audio(sources=['microphone', 'upload'], type='filepath'), | |
| outputs='text' | |
| ) | |
| iface.launch(share=True) | |