Create new file

util.py

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+import streamlit as st
+import torch
+from transformers import BertTokenizer, BertModel
+from huggingface_hub import hf_hub_url, cached_download
+
+def get_cls_layer():
+  config_file_url = hf_hub_url("furrutiav/beto_coherence", filename="cls_layer.torch")
+  value = cached_download(config_file_url)
+  return torch.load(value, map_location=torch.device('cpu'))
+ 
+ get_cls_layer()