finished app no frills

app.py

@@ -1,25 +1,15 @@
 import streamlit as st
 
-x = st.slider("Select a value")
-st.write(x, "squared is", x * x)
+# x = st.slider("Select a value")
+# st.write(x, "squared is", x * x)
 
-# -*- coding: utf-8 -*-
-"""Accelerator_Model_Training_Notebook.ipynb
-
-Automatically generated by Colaboratory.
+st.title("Auto Image classifier training and inference: Imagnet Weights")
 
+# -*- coding: utf-8 -*-
+"""
 Original file is located at
     https://colab.research.google.com/drive/1CSyAE9DhwGTl7bLaSoo7QSyMuoEqJpCj
 
-##This is the Image Classification Model Training Accelerator Notebook
-
- In this notebook, you will input your labelbox API Key, the Model Run ID and Ontology ID associated with the dataset you created using the labelbox platform.
-
- Please note this Notebook will run through given you have followed the beginning of the accelerator tutorial and set up a project that labels **images as one option of a radio classification list**.
-
- label names must be lower case.
-
- Inout your API_Key, Ontology_ID, and Model_Run_ID
 """
 
 def train_and_inference(api_key, ontology_id, model_run_id):