Update app.py

app.py

@@ -357,10 +357,7 @@ def clean_text(text,doc=False,plain_text=False,url=False):
         
         return None, clean_text
         
-# Load all different models (cached) at start time of the hugginface space
-sentence_embedding_model = get_sentence_embedding_model()
-ner_model = get_transformer_pipeline()
-nlp = get_spacy()
+
   
 @st.experimental_singleton
 def get_spacy():
@@ -388,6 +385,11 @@ def get_ner_pipeline():
     tokenizer = AutoTokenizer.from_pretrained("xlm-roberta-large-finetuned-conll03-english")
     model = AutoModelForTokenClassification.from_pretrained("xlm-roberta-large-finetuned-conll03-english")
     return pipeline("ner", model=model, tokenizer=tokenizer, grouped_entities=True)
+
+# Load all different models (cached) at start time of the hugginface space
+sentence_embedding_model = get_sentence_embedding_model()
+ner_model = get_transformer_pipeline()
+nlp = get_spacy()
     
 #Streamlit App