Update app.py

app.py

@@ -9,9 +9,9 @@ model_checkpoint = "vives/distilbert-base-uncased-finetuned-cvent-2019_2022"
 model = AutoModelForMaskedLM.from_pretrained(model_checkpoint, output_hidden_states=True)
 tokenizer = AutoTokenizer.from_pretrained(model_checkpoint)
 text = st.text_input("Enter word or key-phrase")
-exclude_words = st.radio("exclude_words",[True,False], help="Exclude results that contain any words in the query (i.e exclude 'hot coffee' if the query is 'coffee'")
+exclude_words = st.radio("exclude_words",[True,False], help="Exclude results that contain any words in the query (i.e exclude 'hot coffee' if the query is 'cold coffee')")
 
-exclude_text = st.radio("exclude_text",[True,False], help="Exclude results that contain the query (i.e exclude 'tomato soup recipe' if the query is 'tomato soup'")
+exclude_text = st.radio("exclude_text",[True,False], help="Exclude results that contain the query (i.e exclude 'tomato soup recipe' if the query is 'tomato soup')")
 k = st.number_input("Top k nearest key-phrases",1,10,5)
 
 with open("kp_dict_merged.pickle",'rb') as handle: