Update s.py

s.py

@@ -1,20 +1,5 @@
-from transformers import AutoModelForCausalLM, AutoTokenizer
-import torch
+from transformers import AutoTokenizer, AutoModelForCausalLM
 
+tokenizer = AutoTokenizer.from_pretrained("satvikag/chatbot")
 
-tokenizer = AutoTokenizer.from_pretrained("microsoft/DialoGPT-small")
-model = AutoModelForCausalLM.from_pretrained("microsoft/DialoGPT-small")
-
-# Let's chat for 5 lines
-for step in range(5):
-    # encode the new user input, add the eos_token and return a tensor in Pytorch
-    new_user_input_ids = tokenizer.encode(input(">> User:") + tokenizer.eos_token, return_tensors='pt')
-
-    # append the new user input tokens to the chat history
-    bot_input_ids = torch.cat([chat_history_ids, new_user_input_ids], dim=-1) if step > 0 else new_user_input_ids
-
-    # generated a response while limiting the total chat history to 1000 tokens, 
-    chat_history_ids = model.generate(bot_input_ids, max_length=1000, pad_token_id=tokenizer.eos_token_id)
-
-    # pretty print last ouput tokens from bot
-    print("DialoGPT: {}".format(tokenizer.decode(chat_history_ids[:, bot_input_ids.shape[-1]:][0], skip_special_tokens=True)))
+model = AutoModelForCausalLM.from_pretrained("satvikag/chatbot")