update readme

README.md

@@ -41,18 +41,10 @@ print(response)
 
 ### AgentLMs as service
 We recommend using [vLLM](https://github.com/vllm-project/vllm) and [FastChat](https://github.com/lm-sys/FastChat) to deploy the model inference service. First, you need to install the corresponding packages (for detailed usage, please refer to the documentation of the two projects):
-1. For Qwen-7B-MAT, install the corresponding packages with the following commands
 ```bash
 pip install vllm
 pip install "fschat[model_worker,webui]"
 ```
-2. For Baichuan-13B-MAT, install the corresponding packages with the following commands
-```bash
-pip install "fschat[model_worker,webui]"
-pip install vllm==0.2.0
-pip install transformers==4.33.2
-```
-
 To deploy KAgentLMs, you first need to start the controller in one terminal.
 ```bash
 python -m fastchat.serve.controller
@@ -73,5 +65,4 @@ Finally, you can use the curl command to invoke the model same as the OpenAI cal
 curl http://localhost:8888/v1/chat/completions \
 -H "Content-Type: application/json" \
 -d '{"model": "kagentlms_qwen_7b_mat", "messages": [{"role": "user", "content": "Who is Andy Lau"}]}'
-```
-Here, change `kagentlms_qwen_7b_mat` to the model you deployed.
+```