Upload folder using huggingface_hub

app.py

@@ -5,6 +5,14 @@ from transformers import pipeline
 model_id = "Sandiago21/whisper-large-v2-greek"  # update with your model id
 pipe = pipeline("automatic-speech-recognition", model=model_id)
 
+
+title = "Automatic Speech Recognition (ASR)"
+description = """
+Demo for automatic speech recognition in Greek. Demo uses [Sandiago21/whisper-large-v2-greek](https://huggingface.co/Sandiago21/whisper-large-v2-greek) checkpoint, which is based on OpenAI's
+[Whisper](https://huggingface.co/openai/whisper-large-v2) model and is fine-tuned in Greek Audio dataset
+![Automatic Speech Recognition (ASR)"](https://datasets-server.huggingface.co/assets/huggingface-course/audio-course-images/--/huggingface-course--audio-course-images/train/2/image/image.png "Diagram of Automatic Speech Recognition (ASR)")
+"""
+
 def transcribe_speech(filepath):
     output = pipe(
         filepath,
@@ -36,6 +44,9 @@ with demo:
     gr.TabbedInterface(
         [mic_transcribe, file_transcribe],
         ["Transcribe Microphone", "Transcribe Audio File"],
-    )
+    ),
+    examples=[["./example.wav"]],
+    tilte=title,
+    description=description,
 
 demo.launch()