Update app.py

app.py

@@ -23,15 +23,15 @@ input_text = st.text_input("Testo:", value="Lorem ipsum dolor sit amet, [MASK] a
 # Model based on BERT
 #modelname = "./models/latin_bert/"
 #Hugging face LuisAVasquez/simple-latin-bert-uncased
-modelname_lv = "LuisAVasquez/simple-latin-bert-uncased"
+#modelname_lv = "LuisAVasquez/simple-latin-bert-uncased"
 #https://github.com/dbamman/latin-bert
 modelname = "./models/bert-base-latin-uncased"
 
 
 
-tokenizer_roberta = AutoTokenizer.from_pretrained("pstroe/roberta-base-latin-cased3")
-model_roberta = AutoModelForMaskedLM.from_pretrained("pstroe/roberta-base-latin-cased3")
-fill_mask_roberta = pipeline("fill-mask", model=model_roberta, tokenizer=tokenizer_roberta)
+#tokenizer_roberta = AutoTokenizer.from_pretrained("pstroe/roberta-base-latin-cased3")
+#model_roberta = AutoModelForMaskedLM.from_pretrained("pstroe/roberta-base-latin-cased3")
+#fill_mask_roberta = pipeline("fill-mask", model=model_roberta, tokenizer=tokenizer_roberta)
 
 tokenizer_robertaclasscat = AutoTokenizer.from_pretrained("ClassCat/roberta-base-latin-v2")
 model_robertaclasscat = AutoModelForMaskedLM.from_pretrained("ClassCat/roberta-base-latin-v2")
@@ -41,22 +41,22 @@ tokenizer = AutoTokenizer.from_pretrained(modelname)
 model = AutoModelForMaskedLM.from_pretrained(modelname)
 fill_mask = pipeline("fill-mask", model=model, tokenizer=tokenizer)
 
-tokenizer_lv = AutoTokenizer.from_pretrained(modelname_lv)
-model_lv = AutoModelForMaskedLM.from_pretrained(modelname_lv)
-fill_mask_lv = pipeline("fill-mask", model=model_lv, tokenizer=tokenizer_lv)
+#tokenizer_lv = AutoTokenizer.from_pretrained(modelname_lv)
+#model_lv = AutoModelForMaskedLM.from_pretrained(modelname_lv)
+#fill_mask_lv = pipeline("fill-mask", model=model_lv, tokenizer=tokenizer_lv)
 
 if input_text:
     predictions = fill_mask(input_text)
-    st.subheader("Risultati delle previsioni con Bert Base Latin Uncased:")
+    st.subheader("Risultati delle previsioni con Bert:")
     for pred in predictions:
         st.write(f"**Parola**: {pred['token_str']}, **Probabilità**: {pred['score']:.4f}, **Sequence**: {pred['sequence']}")
-    input_text_roberta = input_text.replace("[MASK]", "<mask>")
-    predictions_roberta = fill_mask_roberta(input_text_roberta)    
-    st.subheader("Risultati delle previsioni con Roberta Base Latin Cased 3:")
-    for pred_roberta in predictions_roberta:
-        st.write(f"**Parola**: {pred_roberta['token_str']}, **Probabilità**: {pred_roberta['score']:.4f}, **Sequence**: {pred_roberta['sequence']}")
+    #input_text_roberta = input_text.replace("[MASK]", "<mask>")
+    #predictions_roberta = fill_mask_roberta(input_text_roberta)    
+    #st.subheader("Risultati delle previsioni con Roberta Base Latin Cased 3:")
+    #for pred_roberta in predictions_roberta:
+    #    st.write(f"**Parola**: {pred_roberta['token_str']}, **Probabilità**: {pred_roberta['score']:.4f}, **Sequence**: {pred_roberta['sequence']}")
     predictions_robertaclasscat = fill_mask_robertaclasscat(input_text_roberta)    
-    st.subheader("Risultati delle previsioni con Roberta Base Latin ClassCat V2:")
+    st.subheader("Risultati delle previsioni con Roberta:")
     for pred_robertaclasscat in predictions_robertaclasscat:
         st.write(f"**Parola**: {pred_robertaclasscat['token_str']}, **Probabilità**: {pred_robertaclasscat['score']:.4f}, **Sequence**: {pred_robertaclasscat['sequence']}")