Adapted to the final model.

app.py

@@ -85,7 +85,7 @@ def evaluate_stream(msg, history, temperature, top_p):
     context = context.replace(r'<br>', '')
 
     # TODO: Avoid the tokens are too long.
-    CUTOFF = 256 
+    CUTOFF = 208
     while len(tokenizer.encode(context)) > CUTOFF:
         # save 15 token size for the answer
         context = context[15:]
@@ -112,9 +112,9 @@ with gr.Blocks() as demo:
     state = gr.State()
     with gr.Row():
         with gr.Column(scale=2):
-            temp = gr.components.Slider(minimum=0, maximum=1.1, value=0.95, label="Temperature",
-                info="温度参数，越高的温度生成的内容越丰富，但是有可能出现语法问题。")
-            top_p = gr.components.Slider(minimum=0.5, maximum=1.0, value=0.975, label="Top-p",
+            temp = gr.components.Slider(minimum=0, maximum=1.1, value=0.75, label="Temperature",
+                info="温度参数，越高的温度生成的内容越丰富，但是有可能出现语法问题。小的温度也能帮助生成更相关的回答。")
+            top_p = gr.components.Slider(minimum=0.5, maximum=1.0, value=0.98, label="Top-p",
                 info="top-p参数，只输出前p>top-p的文字，越大生成的内容越丰富，但也可能出现语法问题。数字越小似乎上下文的衔接性越好。")
             #code = gr.Textbox(label="temp_output", info="解码器输出")
             #top_k = gr.components.Slider(minimum=1, maximum=200, step=1, value=25, label="Top k",