update code

app.py

@@ -1,28 +1,36 @@
 import gradio as gr
 from transformers import AutoTokenizer, AutoModel
+from transformers import GPT2Tokenizer,GPT2LMHeadModel
 
 def chat(prompt):
 
     global model, tokenizer
-    response, history = model.chat(tokenizer,
-                                   prompt,
-                                   history=None,
-                                   max_length=64,
-                                   top_p=0.7,
-                                   temperature=0.95,
-                                   num_beam_groups=1,
-                                   num_beams=2
-                                   )
+    inputs = tokenizer(prompt, return_tensors='pt')
+    generation_output = model.generate(**inputs,
+                                       return_dict_in_generate=True,
+                                       output_scores=True,
+                                       max_length=150,
+                                       # max_new_tokens=80,
+                                       do_sample=True,
+                                       top_p=0.6,
+                                       # num_beams=5,
+                                       eos_token_id=50256,
+                                       pad_token_id=0,
+                                       num_return_sequences=1)
 
-    return response
+    for idx, sentence in enumerate(generation_output.sequences):
+
+              return tokenizer.decode(sentence).split('<|endoftext|>')[0]
 
 
 
 
 
 if __name__ == '__main__':
-    tokenizer = AutoTokenizer.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True)
-    model = AutoModel.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True).float()
+    hf_model_path = 'IDEA-CCNL/Yuyuan-GPT2-110M-SciFi-Chinese'
+    tokenizer = GPT2Tokenizer.from_pretrained(hf_model_path)
+    model = GPT2LMHeadModel.from_pretrained(hf_model_path)
+
     model.eval()
     iface = gr.Interface(fn=chat, inputs="text", outputs="text")
     iface.launch()