updated style

app.py

@@ -2,9 +2,8 @@ from transformers import pipeline
 import gradio as gr
 import os
 
-# Load the ASR model
-asr = pipeline(task="automatic-speech-recognition",
-               model="distil-whisper/distil-small.en")
+# Load the ASR model from Hugging Face Hub
+asr = pipeline(task="automatic-speech-recognition", model="openai/whisper-small")
 
 # Define the transcription function
 def transcribe_long_form(filepath):
@@ -13,13 +12,21 @@ def transcribe_long_form(filepath):
     output = asr(filepath)
     return output['text']
 
+# Custom CSS to improve the interface
+css = """
+body { font-family: Arial, sans-serif; }
+button { background-color: #4CAF50; color: white; border: none; padding: 10px 20px; }
+"""
+
 # Set up the Gradio interface
-with gr.Blocks() as demo:
+with gr.Blocks(css=css) as demo:
+    gr.Markdown("### Audio Transcription Service")
+    gr.Markdown("Upload an audio file or use your microphone to record one. Then press the 'Transcribe' button to see the transcription.")
     with gr.Tab("Transcribe Audio"):
         with gr.Row():
-            audio_input = gr.Audio(sources=["microphone", "upload"], type="filepath")
+            audio_input = gr.Audio(sources=["microphone", "upload"], type="filepath", label="Upload or Record Audio")
             submit_button = gr.Button("Transcribe")
-        transcription_output = gr.Textbox(label="Transcription", lines=3)
+        transcription_output = gr.Textbox(label="Transcription", lines=10, placeholder="Your transcription will appear here...")
 
         submit_button.click(
             transcribe_long_form,