File size: 637 Bytes
e6b203c
 
 
50d8c8c
e6b203c
0e661e2
 
 
e6b203c
479a553
e6b203c
 
50d8c8c
e6b203c
0e661e2
 
e6b203c
 
50d8c8c
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
import whisper
import gradio as gr

model = whisper.load_model("base")

def transcribe(audio_filepath):
    print(f"πŸ” Received file: {audio_filepath}")
    result = model.transcribe(audio_filepath, language="en")
    return result["text"]
print('enter')
iface = gr.Interface(
    fn=transcribe,
    inputs=gr.Audio(type="filepath", label="audio_filepath"),
    outputs="text",
    title="Whisper Transcription (English Only)",
    description="Upload an English audio file to get transcription using OpenAI's Whisper."
)

# βœ… Compatible way for Spaces β€” don't use `enable_queue` if Gradio version < 3.30+
iface.launch(share=True)