commit from

app.py

@@ -1,5 +1,6 @@
 import streamlit as st
 import numpy as np
+from transformers import AutoTokenizer, AutoModel
 
 my_model_name = "istassiy/ysda_2022_ml2_hw3_distilbert_base_uncased"
 
@@ -37,12 +38,15 @@ sorted_arxiv_topics = sorted(set(arxiv_code_to_topic.values()))
 
 NUM_LABELS = len(sorted_arxiv_topics)
 
-@st.cache
-def load_model():
-  from transformers import AutoTokenizer, AutoModel
+@st.cache(hash_funcs={AutoTokenizer: id})
+def load_tokenizer():
   tokenizer = AutoTokenizer.from_pretrained(my_model_name)
+  return tokenizer
+
+@st.cache(hash_funcs={AutoModel: id})
+def load_model():
   model = AutoModel.from_pretrained(my_model_name)
-  return tokenizer, model
+  return model
 
 def sigmoid(x):
   return 1/(1 + np.exp(-x))
@@ -60,7 +64,8 @@ def get_top_predictions(predictions):
       break
   return res
 
-tokenizer, model = load_model()
+tokenizer = load_tokenizer()
+model = load_model()
 
 st.markdown("# Scientific paper classificator")
 st.markdown(