update app readme

app.py

@@ -9,6 +9,7 @@ import os
 import time
 import plotly.express as px
 import plotly.graph_objects as go
+from PIL import Image
 global _plotly_config
 _plotly_config={'displayModeBar': False}
 
@@ -229,18 +230,15 @@ def zs_mlm_task_selected(task,
 
 ############## Pre-Download & instantiate objects for Zero shot MLM analysis ********************* END **********************************
 
+# Image.open('hf_space1.png').convert('RGB').save('hf_space1.png')
+img = Image.open("hf_space1.png")
 
 if select_task=='README':
     st.header("NLP Summary")
-    st.write(f"The current App deployed in Huggingface Space has {total_threads} CPU cores but only 1 is available per user so "
+    st.write(f"The App gives you ability to 1) Detect Sentiment, 2) Zeroshot Classification.Currently.It has {total_threads} CPU cores but only 1 is available per user so "
              f"inference time will be on the higher side.")
     st.markdown("---")
-    st.subheader("Info on Zeroshot Text Classification")
-    st.write("* It has been implemented using 2 novel approaches")
-    st.write("1. Using Natural Language Inference")
-    st.write("2. Using Masked language Model")
-    st.write("Relevant Paper - https://paperswithcode.com/paper/zero-shot-text-classification-with-generative")
-    st.markdown()
+    st.image(img)
 
 if select_task == 'Detect Sentiment':
     t1=time.time()

zeroshot_clf_helper.py

@@ -5,7 +5,6 @@ import subprocess
 import numpy as np
 import pandas as pd
 import transformers
-import transformers.convert_graph_to_onnx as onnx_convert
 from pathlib import Path
 import streamlit as st