Update app.py

app.py

@@ -8,7 +8,7 @@ import numpy as np
 import itertools
 import tokenizers
 
-@st.cache(hash_funcs={tokenizers.Tokenizer: lambda _: None, AutoModelForMaskedLM:lambda _: None})
+@st.cache(hash_funcs={tokenizers.Tokenizer: lambda _: None, AutoModelForMaskedLM: lambda _: None})
 def load_bert():
   return (AutoModelForMaskedLM.from_pretrained("vives/distilbert-base-uncased-finetuned-cvent-2019_2022", output_hidden_states=True),
   AutoTokenizer.from_pretrained("vives/distilbert-base-uncased-finetuned-cvent-2019_2022"))
@@ -17,7 +17,7 @@ model, tokenizer = load_bert()
 kp_dict_checkpoint = "kp_dict_merged.pickle"
 kp_cosine_checkpoint = "cosine_kp.pickle"
 
-@st.cache
+@st.cache(hash_funcs={tokenizers.Tokenizer: lambda _: None, AutoModelForSequenceClassification: lambda _: None})
 def load_finbert():
   return (AutoModelForSequenceClassification.from_pretrained("ProsusAI/finbert", output_hidden_states=True),
   AutoTokenizer.from_pretrained("ProsusAI/finbert"))
@@ -26,7 +26,7 @@ model_finbert, tokenizer_finbert = load_finbert()
 kp_dict_finbert_checkpoint = "kp_dict_finance.pickle"
 kp_cosine_finbert_checkpoint = "cosine_kp_finance.pickle"
 
-@st.cache
+@st.cache(hash_funcs={tokenizers.Tokenizer: lambda _: None, AutoModel: lambda _: None})
 def load_sapbert():
   return (AutoModel.from_pretrained("cambridgeltl/SapBERT-from-PubMedBERT-fulltext", output_hidden_states=True),
   AutoTokenizer.from_pretrained("cambridgeltl/SapBERT-from-PubMedBERT-fulltext"))