Update app.py

app.py

@@ -1,7 +1,7 @@
+import spaces
 import gradio as gr
 import numpy as np
 import torch
-import spaces
 from peft import PeftModel, PeftConfig
 from transformers import WhisperForConditionalGeneration, WhisperTokenizer, WhisperProcessor, AutomaticSpeechRecognitionPipeline
 
@@ -28,8 +28,7 @@ def transcribe(audio):
     sr, y = audio
     y = y.astype(np.float32)
     y /= np.max(np.abs(y))
-    with torch.cuda.amp.autocast():
-        return pipeline({"sampling_rate": sr, "raw": y}, generate_kwargs={"forced_decoder_ids": forced_decoder_ids}, max_new_tokens=255)["text"]
+    return pipeline({"sampling_rate": sr, "raw": y}, generate_kwargs={"forced_decoder_ids": forced_decoder_ids}, max_new_tokens=255)["text"]
 
 examples = [
     "./examples/audio_1.mp3",