Update app.py

app.py

@@ -10,16 +10,14 @@ import os
 access_token=os.getenv("access_token")
 
 MODEL_NAME = "openai/whisper-large-v3"
-BATCH_SIZE = 8
-FILE_LIMIT_MB = 1000
-YT_LENGTH_LIMIT_S = 3600  # limit to 1 hour YouTube files
+BATCH_SIZE = 3
 
 device = 0 if torch.cuda.is_available() else "cpu"
 
 pipe = pipeline(
     task="automatic-speech-recognition",
     model=MODEL_NAME,
-    chunk_length_s=30,
+    #chunk_length_s=30,
     device=device,
     token=access_token
 )
@@ -28,7 +26,7 @@ pipe = pipeline(
 def transcribe(inputs, task):
     if inputs is None:
         raise gr.Error("No audio file submitted! Please upload or record an audio file before submitting your request.")
-    text = pipe(inputs[1], batch_size=BATCH_SIZE, generate_kwargs={"task": task}, return_timestamps=True)["text"]
+    text = pipe(inputs[1], batch_size=BATCH_SIZE, generate_kwargs={"task": task})["text"]
     return  text