Try out better caching for the pipeline

app.py

@@ -1,6 +1,8 @@
 import pandas as pd
 import streamlit as st
-from transformers import pipeline
+import tokenizers
+import torch
+from transformers import Pipeline, pipeline
 
 st.set_page_config(
     page_title="Zero-shot classification from tabular data",
@@ -10,8 +12,21 @@ st.set_page_config(
     menu_items=None,
 )
 
-with st.spinner("Setting stuff up related to the inference engine..."):
+
+@st.cache(
+    hash_funcs={
+        torch.nn.parameter.Parameter: lambda _: None,
+        tokenizers.Tokenizer: lambda _: None,
+        tokenizers.AddedToken: lambda _: None,
+    },
+    allow_output_mutation=True,
+)
+def load_classifier() -> Pipeline:
     classifier = pipeline("zero-shot-classification", model="facebook/bart-large-mnli")
+    return classifier
+
+
+classifier = load_classifier()
 
 st.title("Zero-shot classification from tabular data")
 st.text(