diff --git a/README.md b/README.md
index 928c564..d914982 100644
--- a/README.md
+++ b/README.md
@@ -109,7 +109,7 @@ python inference.py --model_path <vllmcpm_repo_path> --prompt_path prompts/promp
 ```
 
 #### Huggingface 模型
-（注：我们发现当前Huggingface的推理代码推理效果差于Vllm的推理代码，我们正在对齐中，请耐心等待）
+（注：我们发现当前Huggingface的推理代码推理效果差于Vllm的推理代码，我们正在对齐中，目前已定为到PageAttention和普通attention的区别，请耐心等待）
 ##### MiniCPM-2B
 * 安装`transformers>=4.36.0`以及`accelerate`后，运行以下代码
 ```python
diff --git a/demo/hf_based_demo.py b/demo/hf_based_demo.py
index 38c5457..88bda71 100644
--- a/demo/hf_based_demo.py
+++ b/demo/hf_based_demo.py
@@ -14,7 +14,9 @@ from transformers import (
 
 parser = argparse.ArgumentParser()
 parser.add_argument("--model_path", type=str, default="")
-parser.add_argument("--torch_dtype", type=str, default="bfloat16")
+parser.add_argument("--torch_dtype", type=str, default="bfloat16", choices=["float32", "bfloat16"]))
+parser.add_argument("--server_name", type=str, default="127.0.0.1")
+parser.add_argument("--server_port", type=int, default=7860)
 args = parser.parse_args()
 
 # init model torch dtype
@@ -31,6 +33,9 @@ path = args.model_path
 tokenizer = AutoTokenizer.from_pretrained(path)
 model = AutoModelForCausalLM.from_pretrained(path, torch_dtype=torch_dtype, device_map="auto", trust_remote_code=True)
 
+# init gradio demo host and port
+server_name=args.server_name
+server_port=args.server_port
 
 def hf_gen(dialog: List, top_p: float, temperature: float, max_dec_len: int):
     """generate model output with huggingface api
@@ -161,4 +166,4 @@ with gr.Blocks(theme="soft") as demo:
     reverse.click(reverse_last_round, inputs=[chatbot], outputs=[chatbot])
 
 demo.queue()
-demo.launch(server_name="127.0.0.1", show_error=True)
+demo.launch(server_name=server_name, server_port=server_port, show_error=True)
diff --git a/demo/vllm_based_demo.py b/demo/vllm_based_demo.py
index 802c79c..0180405 100644
--- a/demo/vllm_based_demo.py
+++ b/demo/vllm_based_demo.py
@@ -9,7 +9,9 @@ from vllm import LLM, SamplingParams
 
 parser = argparse.ArgumentParser()
 parser.add_argument("--model_path", type=str, default="")
-parser.add_argument("--torch_dtype", type=str, default="bfloat16")
+parser.add_argument("--torch_dtype", type=str, default="bfloat16", choices=["float32", "bfloat16"]))
+parser.add_argument("--server_name", type=str, default="127.0.0.1")
+parser.add_argument("--server_port", type=int, default=7860)
 args = parser.parse_args()
 
 
@@ -26,6 +28,9 @@ else:
 path = args.model_path
 llm = LLM(model=path, tensor_parallel_size=1, dtype=torch_dtype)
 
+# init gradio demo host and port
+server_name=args.server_name
+server_port=args.server_port
 
 def vllm_gen(dialog: List, top_p: float, temperature: float, max_dec_len: int):
     """generate model output with huggingface api
@@ -169,4 +174,4 @@ with gr.Blocks(theme="soft") as demo:
     reverse.click(reverse_last_round, inputs=[chatbot], outputs=[chatbot])
 
 demo.queue()
-demo.launch(server_name="127.0.0.1", show_error=True)
+demo.launch(server_name=server_name, server_port=server_port, show_error=True)