Update app.py

app.py

@@ -14,18 +14,33 @@ st.header("Knowledge extraction on Endocrine disruptors")
 st.write("This tool lets you extract relation triples concerning interactions between: endocrine disrupting chemicals, hormones, receptors and cancers.")
 st.write("It is the result of an end of studies project within ESI school and dedicated to biomedical researchers looking to extract precise information about the subject without digging into long publications.")
 
+
+@st.cache
+def load_models():
+  tokenizer = AutoTokenizer.from_pretrained("dmis-lab/biobert-large-cased-v1.1", truncation = True, padding=True, model_max_length=512,)
+  model_checkpoint = BertForTokenClassification.from_pretrained("dexay/Ner2HgF", )
+   
+  model_re = AutoModelForSequenceClassification.from_pretrained("dexay/reDs3others", )
+
+
+
 form = st.form(key='my-form')
 x = form.text_area('Enter text', height=250)
 submit = form.form_submit_button('Submit')
 
+
+
+
+
 if submit and len(x) != 0:  
   #model.to("cpu")
   st.text("Execution is in progress ...")
-  tokenizer = AutoTokenizer.from_pretrained("dmis-lab/biobert-large-cased-v1.1", truncation = True, padding=True, model_max_length=512,)
-  model_checkpoint = BertForTokenClassification.from_pretrained("dexay/Ner2HgF", )
+  
+  load_models()
+  
+  
   
   
-  model_re = AutoModelForSequenceClassification.from_pretrained("dexay/reDs3others", )
   token_classifier = pipeline("token-classification", tokenizer = tokenizer,model=model_checkpoint,  )