Update app.py

app.py

@@ -2,11 +2,9 @@ import os
 import gradio as gr
 from faster_whisper import WhisperModel
 from pytube import YouTube
-import torch
 
 # Inicializar el modelo Whisper
-device = "cuda" if torch.cuda.is_available() else "cpu"
-model = WhisperModel("base", device=device, compute_type="float16")
+model = WhisperModel("base", device="cpu", compute_type="int8")
 
 def transcribe_audio(audio_path):
     segments, _ = model.transcribe(audio_path, beam_size=5)
@@ -42,7 +40,7 @@ iface = gr.Interface(
     ],
     outputs="text",
     title="Whisper Transcription App",
-    description="Upload an audio file or provide a YouTube URL to transcribe."
+    description="Upload an audio file or provide a YouTube URL to transcribe. Note: This is running on CPU, so processing might be slower."
 )
 
 # Lanzar la aplicación