Upload 2 files

app.py

@@ -1,12 +1,9 @@
 from transformers import pipeline
 import gradio as gr
-import torch
 
-device = 'cuda' if torch.cuda.is_available else 'cpu'
 
 model = pipeline(
     "automatic-speech-recognition", 
-    device=device, 
     model='openai/whisper-large-v3',
     chunk_length_s=30,
     generate_kwargs={"task": "transcribe"}
@@ -20,13 +17,11 @@ def transcribe_audio(mic=None, file=None, return_timestamps=False):
     else:
         return "You must either provide a mic recording or a file"
         
-    gr.Info(f"Device: {device}") 
-    with torch.no_grad():
-        result = model(audio, return_timestamps=return_timestamps, batch_size=8)
-        if return_timestamps:
-            return result['chunks']
-        else:
-            return result['text']
+    result = model(audio, return_timestamps=return_timestamps, batch_size=8)
+    if return_timestamps:
+        return result['chunks']
+    else:
+        return result['text']
         
 
 gr.Interface(

requirements.txt

@@ -1,2 +1,2 @@
 transformers
-torch
+