Update app.py

app.py

@@ -10,7 +10,7 @@ from PIL import Image
 def get_model(model_name, model_path):
     tokenizer = transformers.GPT2Tokenizer.from_pretrained(model_name)
     tokenizer.add_special_tokens({
-    'eos_token': '[EOS]'
+        'eos_token': '[EOS]'
     })
     model = transformers.GPT2LMHeadModel.from_pretrained(model_name)
     model.resize_token_embeddings(len(tokenizer))
@@ -20,7 +20,7 @@ def get_model(model_name, model_path):
 
 
 #@st.cache(hash_funcs={tokenizers.Tokenizer: lambda _: None, tokenizers.AddedToken: lambda _: None, re.Pattern: lambda _: None}, allow_output_mutation=True, suppress_st_warning=True)
-def predict(text, model, tokenizer, n_beams=5, temperature=2.5, top_p=0.8, max_length=200):
+def predict(text, model, tokenizer, n_beams=5, temperature=2.5, top_p=0.8, max_length=300):
     text += '\n'
     input_ids = tokenizer.encode(text, return_tensors="pt")
     length_of_prompt = len(input_ids[0])
@@ -31,6 +31,7 @@ def predict(text, model, tokenizer, n_beams=5, temperature=2.5, top_p=0.8, max_l
                              temperature=temperature,
                              top_p=top_p,
                              max_length=max_length + length_of_prompt,
+                             eos_token_id=tokenizer.eos_token_id
                              )
 
     return list(map(tokenizer.decode, out))[0]
@@ -59,8 +60,10 @@ if button:
     #for line in lines:
     #    st.write(line)
     
-    lines = result.replace('\n', '\n\n')
-    st.write(lines)
+    #lines = result.replace('\n', '\n\n')
+    #st.write(lines)
+    
+    st.text_area(label='', value=result)
     
     #except Exception:
     #    st.error("Ooooops, something went wrong. Try again please and report to me, tg: @vladyur")