Update app.py

Streamlit st.cache --> st.cache_resource

app.py

@@ -47,19 +47,19 @@ elif input_method == "Write or Paste New Text":
     st.subheader("Text to Run")
     input_text = st.text_area('Write or Paste Text Below', value="", height=128, max_chars=None, key=2)
 
-@st.cache(allow_output_mutation=True)
+@st.cache_resource
 def setModel(model_checkpoint, aggregation):
     model = AutoModelForTokenClassification.from_pretrained(model_checkpoint)
     tokenizer = AutoTokenizer.from_pretrained(model_checkpoint)
     return pipeline('ner', model=model, tokenizer=tokenizer, aggregation_strategy=aggregation)
 
-@st.cache(allow_output_mutation=True)
+@st.cache_resource
 def get_html(html: str):
     WRAPPER = """<div style="overflow-x: auto; border: 1px solid #e6e9ef; border-radius: 0.25rem; padding: 1rem; margin-bottom: 2.5rem">{}</div>"""
     html = html.replace("\n", " ")
     return WRAPPER.format(html)
     
-@st.cache(allow_output_mutation=True)
+@st.cache_resource
 def entity_comb(output):
     output_comb = []
     for ind, entity in enumerate(output):