Update app.py

app.py

@@ -50,10 +50,14 @@ input_text = st.text_area(
 #tokenizer = GPT2Tokenizer.from_pretrained("Cicciokr/GPT2-Latin-GenText")
 model_name = "facebook/mbart-large-50"
 model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
-tokenizer = AutoTokenizer.from_pretrained(model_name)  # Latino (la_XX)
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+
+model_name_mio = "Cicciokr/mbart50-large-latin"
+model_mio = AutoModelForSeq2SeqLM.from_pretrained(model_name_mio)
+tokenizer_mio = AutoTokenizer.from_pretrained(tokenizer_mio)
 #tokenizer.pad_token_id = tokenizer.eos_token_id
 generator = pipeline("text2text-generation", model=model, tokenizer=tokenizer)
-
+generator_mio = pipeline("text2text-generation", model=model_mio, tokenizer=tokenizer_mio)
 
 # Se l'utente ha inserito (o selezionato) un testo
 if input_text:
@@ -77,3 +81,22 @@ if input_text:
     st.write(f" Frase predetta: {generated_text}\n")
     #st.write(f" Frase predetta: {tokenizer.decode(output[0], skip_special_tokens=True)}\n")
     print(output)
+
+    inputs_mio = tokenizer_mio(input_text, return_tensors="pt")
+    #output = model.generate(**inputs, max_length=512, num_return_sequences=1)
+    output_mio = model_mio.generate(
+        **inputs_mio,
+        max_length=512,
+        num_return_sequences=1,
+        do_sample=True,
+        temperature=0.8,
+        top_k=50,
+        top_p=0.95
+    )
+    generated_text_mio = tokenizer_mio.decode(output_mio[0], skip_special_tokens=True)
+    st.subheader("Risultato Mio:")
+    if 'input_text_value_correct' in st.session_state:
+        st.write(f" Parola corretta: {st.session_state['input_text_value_correct']}\n")
+    st.write(f" Frase predetta: {generated_text_mio}\n")
+    #st.write(f" Frase predetta: {tokenizer.decode(output[0], skip_special_tokens=True)}\n")
+    print(output)