update cli_demo.py and web_demo.py

cli_demo.py

@@ -18,8 +18,12 @@ from transformers.trainer_utils import set_seed
 DEFAULT_CKPT_PATH = 'Qwen/Qwen-7B-Chat'
 
 _WELCOME_MSG = '''\
-Welcome to use Qwen-7B-Chat model, type text to start chat, type :h to show command help
+Welcome to use Qwen-Chat model, type text to start chat, type :h to show command help.
-欢迎使用 Qwen-7B 模型，输入内容即可进行对话，:h 显示命令帮助
+(欢迎使用 Qwen-Chat 模型，输入内容即可进行对话，:h 显示命令帮助。)
+
+Note: This demo is governed by the original license of Qwen.
+We strongly advise users not to knowingly generate or allow others to knowingly generate harmful content, including hate speech, violence, pornography, deception, etc.
+(注：本演示受Qwen的许可协议限制。我们强烈建议，用户不应传播及不应允许他人传播以下内容，包括但不限于仇恨言论、暴力、色情、欺诈相关的有害信息。)
 '''
 _HELP_MSG = '''\
 Commands:
@@ -46,17 +50,6 @@ def _load_model_tokenizer(args):
     else:
         device_map = "auto"
 
-    qconfig_path = os.path.join(args.checkpoint_path, 'quantize_config.json')
-    if os.path.exists(qconfig_path):
-        from auto_gptq import AutoGPTQForCausalLM
-        model = AutoGPTQForCausalLM.from_quantized(
-            args.checkpoint_path,
-            device_map=device_map,
-            trust_remote_code=True,
-            resume_download=True,
-            use_safetensors=True,
-        ).eval()
-    else:
     model = AutoModelForCausalLM.from_pretrained(
         args.checkpoint_path,
         device_map=device_map,
@@ -103,7 +96,7 @@ def _get_input() -> str:
 
 def main():
     parser = argparse.ArgumentParser(
-        description='QWen-7B-Chat command-line interactive chat demo.')
+        description='QWen-Chat command-line interactive chat demo.')
     parser.add_argument("-c", "--checkpoint-path", type=str, default=DEFAULT_CKPT_PATH,
                         help="Checkpoint name or path, default to %(default)r")
     parser.add_argument("-s", "--seed", type=int, default=1234, help="Random seed")
@@ -195,7 +188,7 @@ def main():
             for response in model.chat_stream(tokenizer, query, history=history, generation_config=config):
                 _clear_screen()
                 print(f"\nUser: {query}")
-                print(f"\nQwen-7B: {response}")
+                print(f"\nQwen-Chat: {response}")
         except KeyboardInterrupt:
             print('[WARNING] Generation interrupted')
             continue

web_demo.py

@@ -47,17 +47,6 @@ def _load_model_tokenizer(args):
     else:
         device_map = "auto"
 
-    qconfig_path = os.path.join(args.checkpoint_path, 'quantize_config.json')
-    if os.path.exists(qconfig_path):
-        from auto_gptq import AutoGPTQForCausalLM
-        model = AutoGPTQForCausalLM.from_quantized(
-            args.checkpoint_path,
-            device_map=device_map,
-            trust_remote_code=True,
-            resume_download=True,
-            use_safetensors=True,
-        ).eval()
-    else:
     model = AutoModelForCausalLM.from_pretrained(
         args.checkpoint_path,
         device_map=device_map,
@@ -133,7 +122,7 @@ def _launch_demo(args, model, tokenizer, config):
 
         print(f"History: {_task_history}")
         _task_history.append((_query, full_response))
-        print(f"Qwen-7B-Chat: {_parse_text(full_response)}")
+        print(f"Qwen-Chat: {_parse_text(full_response)}")
 
     def regenerate(_chatbot, _task_history):
         if not _task_history:
@@ -156,21 +145,25 @@ def _launch_demo(args, model, tokenizer, config):
 
     with gr.Blocks() as demo:
         gr.Markdown("""\
-<p align="center"><img src="https://modelscope.cn/api/v1/models/qwen/Qwen-7B-Chat/repo?
+<p align="center"><img src="https://qianwen-res.oss-cn-beijing.aliyuncs.com/logo_qwen.jpg" style="height: 80px"/><p>""")
-Revision=master&FilePath=assets/logo.jpeg&View=true" style="height: 80px"/><p>""")
+        gr.Markdown("""<center><font size=8>Qwen-Chat Bot</center>""")
-        gr.Markdown("""<center><font size=8>Qwen-7B-Chat Bot</center>""")
         gr.Markdown(
             """\
-<center><font size=3>This WebUI is based on Qwen-7B-Chat, developed by Alibaba Cloud. \
+<center><font size=3>This WebUI is based on Qwen-Chat, developed by Alibaba Cloud. \
-(本WebUI基于Qwen-7B-Chat打造，实现聊天机器人功能。)</center>""")
+(本WebUI基于Qwen-Chat打造，实现聊天机器人功能。)</center>""")
         gr.Markdown("""\
-<center><font size=4>Qwen-7B <a href="https://modelscope.cn/models/qwen/Qwen-7B/summary">🤖 </a> 
+<center><font size=4>
-| <a href="https://huggingface.co/Qwen/Qwen-7B">🤗</a>&nbsp ｜ 
+Qwen-7B <a href="https://modelscope.cn/models/qwen/Qwen-7B/summary">🤖 </a> | 
+<a href="https://huggingface.co/Qwen/Qwen-7B">🤗</a>&nbsp ｜ 
 Qwen-7B-Chat <a href="https://modelscope.cn/models/qwen/Qwen-7B-Chat/summary">🤖 </a> | 
 <a href="https://huggingface.co/Qwen/Qwen-7B-Chat">🤗</a>&nbsp ｜ 
-&nbsp<a href="https://github.com/QwenLM/Qwen-7B">Github</a></center>""")
+Qwen-14B <a href="https://modelscope.cn/models/qwen/Qwen-14B/summary">🤖 </a> | 
+<a href="https://huggingface.co/Qwen/Qwen-14B">🤗</a>&nbsp ｜ 
+Qwen-14B-Chat <a href="https://modelscope.cn/models/qwen/Qwen-14B-Chat/summary">🤖 </a> | 
+<a href="https://huggingface.co/Qwen/Qwen-14B-Chat">🤗</a>&nbsp ｜ 
+&nbsp<a href="https://github.com/QwenLM/Qwen">Github</a></center>""")
 
-        chatbot = gr.Chatbot(label='Qwen-7B-Chat', elem_classes="control-height")
+        chatbot = gr.Chatbot(label='Qwen-Chat', elem_classes="control-height")
         query = gr.Textbox(lines=2, label='Input')
         task_history = gr.State([])
 
@@ -185,10 +178,10 @@ Qwen-7B-Chat <a href="https://modelscope.cn/models/qwen/Qwen-7B-Chat/summary">
         regen_btn.click(regenerate, [chatbot, task_history], [chatbot], show_progress=True)
 
         gr.Markdown("""\
-<font size=2>Note: This demo is governed by the original license of Qwen-7B. \
+<font size=2>Note: This demo is governed by the original license of Qwen. \
 We strongly advise users not to knowingly generate or allow others to knowingly generate harmful content, \
 including hate speech, violence, pornography, deception, etc. \
-(注：本演示受Qwen-7B的许可协议限制。我们强烈建议，用户不应传播及不应允许他人传播以下内容，\
+(注：本演示受Qwen的许可协议限制。我们强烈建议，用户不应传播及不应允许他人传播以下内容，\
 包括但不限于仇恨言论、暴力、色情、欺诈相关的有害信息。)""")
 
     demo.queue().launch(