Update app.py

app.py

@@ -8,29 +8,29 @@ from transformers import (
 )
 
 # Function to load VQA pipeline
-@st.cache(allow_output_mutation=True)
+@st.cache_resource(allow_output_mutation=True)
 def load_vqa_pipeline():
  return pipeline(task="visual-question-answering", model="dandelin/vilt-b32-finetuned-vqa")
 
 # Function to load BERT-based pipeline
-@st.cache(allow_output_mutation=True)
+@st.cache_resource(allow_output_mutation=True)
 def load_bbu_pipeline():
  return pipeline(task="fill-mask", model="bert-base-uncased")
 
 # Function to load Blenderbot model
-@st.cache(allow_output_mutation=True)
+@st.cache_resource(allow_output_mutation=True)
 def load_blenderbot_model():
  model_name = "facebook/blenderbot-400M-distill"
  tokenizer = BlenderbotTokenizer.from_pretrained(pretrained_model_name_or_path=model_name)
  return BlenderbotForConditionalGeneration.from_pretrained(pretrained_model_name_or_path=model_name)
 
 # Function to load GPT-2 pipeline
-@st.cache(allow_output_mutation=True)
+@st.cache_resource(allow_output_mutation=True)
 def load_gpt2_pipeline():
  return pipeline(task="text-generation", model="gpt2")
 
 # Function to load BERTopic models
-@st.cache(allow_output_mutation=True)
+@st.cache_resource(allow_output_mutation=True)
 def load_topic_models():
  topic_model_1 = BERTopic.load(path="davanstrien/chat_topics")
  topic_model_2 = BERTopic.load(path="MaartenGr/BERTopic_ArXiv")