update

app.py

@@ -9,22 +9,26 @@ model = GPT2LMHeadModel.from_pretrained('NlpHUST/gpt2-vietnamese')
 
 
 def run(text, intensity):
-    res=""
-    max_length=intensity
+    res="NlpHUST model  \n"
+    if (intensity>=10):
+        max_length=intensity
+    else:
+        max_length=10
+        
     input_ids = tokenizer.encode(text, return_tensors='pt')
     sample_outputs = model.generate(input_ids,pad_token_id=tokenizer.eos_token_id,
                                    do_sample=True,
                                    max_length=max_length,
-                                   min_length=max_length,
+                                   min_length=5,
                                    top_k=40,
                                    num_beams=5,
                                    early_stopping=True,
                                    no_repeat_ngram_size=2,
-                                   num_return_sequences=3)
+                                   num_return_sequences=2)
     
     for i, sample_output in enumerate(sample_outputs):
-        res +="Generated text {}\n\n{}".format(i+1, tokenizer.decode(sample_output.tolist()))
-        res +='\n---'
+        res +="Mẫu số {}\n\n{}".format(i+1, tokenizer.decode(sample_output.tolist()))
+        res +='\n'
     return res
 
 demo = gr.Interface(