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import gradio as gr | |
from transformers import pipeline | |
pipeline = pipeline(model="openai/whisper-medium.en") | |
def transcribe(file): | |
options = dict(task="transcribe", best_of=5) | |
text = model.transcribe(file, **options)["text"] | |
return text.strip() | |
block = gr.Blocks() | |
with block: | |
with gr.Group(): | |
audio = gr.Audio( | |
show_label=False, | |
source="microphone", | |
type="filepath" | |
) | |
with gr.Box(): | |
with gr.Row().style(equal_height=True): | |
transcribe_button = gr.Button("Transcribe") | |
textbox = gr.Textbox(show_label=False) | |
transcribe_button.click(transcribe, inputs=[audio], outputs=[textbox]) | |
block.launch(share=True) |