Update app.py

app.py

@@ -1,13 +1,27 @@
 import streamlit as st
+import torch
+import transformers
 
-st.markdown("### Hello, world!")
-st.markdown("<img width=200px src='https://rozetked.me/images/uploads/dwoilp3BVjlE.jpg'>", unsafe_allow_html=True)
+st.markdown("### Articles classificator.")
+# st.markdown("<img width=200px src='https://rozetked.me/images/uploads/dwoilp3BVjlE.jpg'>", unsafe_allow_html=True)
 
-from transformers import pipeline
+@st.cache_data
+def LoadModel():
+    return torch.load('model.pt'), AutoTokenizer.from_pretrained('bert-base-uncased')()
 
-def process(text):
-    return text[::-1]
+model, tokenizer = LoadModel()
 
-text = st.text_area("TEXT HERE")
+def process(title, summary):
+    text = title + summary
+    model.eval()
+    lines = [text]
+    X = tokenizer(lines, padding=True, truncation=True, return_tensors="pt")
+    out = model(X)
+    probs = torch.exp(out[0])
+    return probs
+    
+title = st.text_area("Title")
 
-st.markdown(f"{process(text)}")
+summary = st.text_area("Summary")
+
+st.markdown(f"{process(title, summary)}")