Create app.py

app.py

@@ -0,0 +1,15 @@
+from DistilBERT import model_DB
+import streamlit as st
+from transformers import AutoTokenizer, AutoModel
+import torch
+
+device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
+tokenizer = AutoTokenizer.from_pretrained('distilbert-base-uncased')
+
+def sentiment_analysis_DB(input):
+    encoded_input = tokenizer(text, return_tensors='pt').to(device)
+    model.to(device)
+    ids = 
+    mask = 
+    token_type_ids = 
+    output =