Update app.py

app.py

@@ -4,6 +4,7 @@ import streamlit as st
 import torch
 from transformers import AutoTokenizer, AutoModelForCausalLM 
 
+'''
 tokenizer = AutoTokenizer.from_pretrained(
   'kakaobrain/kogpt', revision='KoGPT6B-ryan1.5b',
   bos_token='[BOS]', eos_token='[EOS]', unk_token='[UNK]', pad_token='[PAD]', mask_token='[MASK]'
@@ -17,16 +18,19 @@ model = AutoModelForCausalLM.from_pretrained(
   torch_dtype=torch.float16, low_cpu_mem_usage=False
 ).to(device=device, non_blocking=True)
 _ = model.eval()
-
+'''
 print("Model loading done!")
 
 def gpt(prompt):
+  return prompt
+  '''
   with torch.no_grad():
     tokens = tokenizer.encode(prompt, return_tensors='pt').to(device=device, non_blocking=True)
     gen_tokens = model.generate(tokens, do_sample=True, temperature=0.8, max_length=256)
     generated = tokenizer.batch_decode(gen_tokens)[0]
 
   return generated
+  '''
     
 #prompts
 st.title("여러분들의 문장을 완성해줍니다. 🤖")