Update app.py

app.py

@@ -2,8 +2,8 @@ import gradio as gr
 import pandas as pd
 from pydub import AudioSegment
 from pyannote.audio import Pipeline
-from transformers import pipeline
-whisper = pipeline('automatic-speech-recognition', model = 'openai/whisper-medium', device = 0)
+import whisper
+model = whisper.load_model("medium")
 pipeline = Pipeline.from_pretrained("pyannote/speaker-diarization",use_auth_token="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")
 def diarization(inp_audio):
     diarization = pipeline(inp_audio)
@@ -35,8 +35,10 @@ def generatetext(filename,starttime,endtime):
   newAudio = AudioSegment.from_wav(filename)
   a = newAudio[t1:t2]
   a.export('audio.wav', format="wav") 
-  text1 = whisper('audio.wav')
-  return text1.get("text")
+  audio = whisper.load_audio('audio.wav')
+  result= model.transcribe(audio)
+  #text1 = whisper('audio.wav')
+  return result.get("text")
 
 block = gr.Blocks()
 with block: