Update app.py

app.py

@@ -1,22 +1,11 @@
 import gradio as gr
 from transformers import pipeline
 
-# Load the default speech recognition model pipeline from Hugging Face
-asr_pipeline = pipeline("automatic-speech-recognition")
-
-# Define a Gradio interface to listen to microphone input and display the transcribed text
-def transcribe_audio():
-    # Listen to microphone input
-    audio_input = gr.audio_input()
-    # Transcribe speech
-    transcription = asr_pipeline(audio_input)
-    return transcription[0]["transcription"]
-
-# Define Gradio interface
-gr.Interface(
-    fn=transcribe_audio,
-    inputs=gr.inputs.Microphone(label="Speak into the microphone"),
-    outputs="text",
-    title="Speech-to-Text with Default Model",
-    description="Speak into the microphone and see the text transcription.",
-).launch()
+pipe = pipeline(task="image-classification", 
+                 # model that can do 22k-category classification
+                 model="microsoft/beit-base-patch16-224-pt22k-ft22k")
+gr.Interface.from_pipeline(pipe, 
+                           title="22k Image Classification",
+                           description="Object Recognition using Microsoft BEIT",
+                           examples = ['wonder_cat.jpg', 'aki_dog.jpg',],
+                           allow_flagging="never").launch(inbrowser=True)