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Update app.py
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app.py
CHANGED
@@ -11,10 +11,13 @@ st.write("Inserisci un testo con il token [MASK] per vedere le previsioni del mo
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st.write("Esempi di testo:");
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st.write("
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st.write("hanno et mago qui [MASK] punico bello cornelium consulem aput liparas ceperunt");
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input_text = st.text_input("Testo:", value="Lorem ipsum dolor sit amet, [MASK] adipiscing elit.")
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# Model based on BERT
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@@ -30,6 +33,10 @@ tokenizer_roberta = AutoTokenizer.from_pretrained("pstroe/roberta-base-latin-cas
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model_roberta = AutoModelForMaskedLM.from_pretrained("pstroe/roberta-base-latin-cased3")
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fill_mask_roberta = pipeline("fill-mask", model=model_roberta, tokenizer=tokenizer_roberta)
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tokenizer = AutoTokenizer.from_pretrained(modelname)
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model = AutoModelForMaskedLM.from_pretrained(modelname)
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fill_mask = pipeline("fill-mask", model=model, tokenizer=tokenizer)
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@@ -52,5 +59,9 @@ if input_text:
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st.subheader("Risultati delle previsioni con Roberta Base Latin Cased 3:")
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for pred_roberta in predictions_roberta:
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st.write(f"**Parola**: {pred_roberta['token_str']}, **Probabilità**: {pred_roberta['score']:.4f}, **Sequence**: {pred_roberta['sequence']}")
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st.write("Esempi di testo:");
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st.write("Asdrubal, frater Annibalis, qui secundo Punico bello [MASK] ingentibus copiis ab Hispania veniens => cum");
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st.write("hanno et mago qui [MASK] punico bello cornelium consulem aput liparas ceperunt => primo");
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st.write("Lorem ipsum dolor sit amet, [MASK] adipiscing elit. => consectetur");
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st.write("Populus Romanus cum Macedonibus [MASK] ter gessit => bellum");
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#Asdrubal, frater Annibalis, qui secundo Punico bello [MASK] ingentibus copiis ab Hispania veniens => cum
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#hanno et mago qui [MASK] punico bello cornelium consulem aput liparas ceperunt => primo
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#Lorem ipsum dolor sit amet, [MASK] adipiscing elit. => consectetur
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input_text = st.text_input("Testo:", value="Lorem ipsum dolor sit amet, [MASK] adipiscing elit.")
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# Model based on BERT
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model_roberta = AutoModelForMaskedLM.from_pretrained("pstroe/roberta-base-latin-cased3")
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fill_mask_roberta = pipeline("fill-mask", model=model_roberta, tokenizer=tokenizer_roberta)
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tokenizer_robertaclasscat = AutoTokenizer.from_pretrained("ClassCat/roberta-base-latin-v2")
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model_robertaclasscat = AutoModelForMaskedLM.from_pretrained("ClassCat/roberta-base-latin-v2")
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fill_mask_robertaclasscat = pipeline("fill-mask", model=model_robertaclasscat, tokenizer=tokenizer_robertaclasscat)
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tokenizer = AutoTokenizer.from_pretrained(modelname)
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model = AutoModelForMaskedLM.from_pretrained(modelname)
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fill_mask = pipeline("fill-mask", model=model, tokenizer=tokenizer)
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st.subheader("Risultati delle previsioni con Roberta Base Latin Cased 3:")
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for pred_roberta in predictions_roberta:
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st.write(f"**Parola**: {pred_roberta['token_str']}, **Probabilità**: {pred_roberta['score']:.4f}, **Sequence**: {pred_roberta['sequence']}")
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predictions_robertaclasscat = fill_mask_robertaclasscat(input_text)
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st.subheader("Risultati delle previsioni con Roberta Base Latin ClassCat V2:")
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for pred_robertaclasscat in predictions_robertaclasscat:
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st.write(f"**Parola**: {pred_robertaclasscat['token_str']}, **Probabilità**: {pred_robertaclasscat['score']:.4f}, **Sequence**: {pred_robertaclasscat['sequence']}")
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