Aggiunto Modello LuisVasquez

app.py

@@ -14,7 +14,7 @@ input_text = st.text_input("Testo:", value="Lorem ipsum dolor sit amet, [MASK] a
 
 # Model based on BERT
 #modelname = "./models/latin_bert/"
-#modelname = "LuisAVasquez/simple-latin-bert-uncased"
+modelname_lv = "LuisAVasquez/simple-latin-bert-uncased"
 modelname = "./models/bert-base-latin-uncased"
 
 
@@ -22,10 +22,18 @@ 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)
+
 if input_text:
     predictions = fill_mask(input_text)
-    st.subheader("Risultati delle previsioni con Simple Latin Bert:")
+    st.subheader("Risultati delle previsioni con Bert Base Latin Uncased:")
     for pred in predictions:
         st.write(f"**Parola**: {pred['token_str']}, **Probabilità**: {pred['score']:.4f}, **Sequence**: {pred['sequence']}")
+    predictions_lv = fill_mask_lv(input_text)
+    st.subheader("Risultati delle previsioni con Simple Latin Bert:")
+    for pred_lv in predictions_lv:
+        st.write(f"**Parola**: {pred_lv['token_str']}, **Probabilità**: {pred_lv['score']:.4f}, **Sequence**: {pred_lv['sequence']}")