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README.md

@@ -499,7 +499,7 @@ print(sess.response.text)
 LMDeploy's `api_server` enables models to be easily packed into services with a single command. The provided RESTful APIs are compatible with OpenAI's interfaces. Below are an example of service startup:
 
 ```shell
-lmdeploy serve api_server OpenGVLab/Mini-InternVL-Chat-2B-V1-5 --model-name Mini-InternVL-Chat-2B-V1-5 --backend turbomind --server-port 23333
+lmdeploy serve api_server OpenGVLab/Mini-InternVL-Chat-2B-V1-5 --backend turbomind --server-port 23333
 ```
 
 To use the OpenAI-style interface, you need to install OpenAI:
@@ -516,7 +516,7 @@ from openai import OpenAI
 client = OpenAI(api_key='YOUR_API_KEY', base_url='http://0.0.0.0:23333/v1')
 model_name = client.models.list().data[0].id
 response = client.chat.completions.create(
-    model="Mini-InternVL-Chat-2B-V1-5",
+    model=model_name,
     messages=[{
         'role':
         'user',
@@ -546,7 +546,7 @@ TODO
 
 ## License
 
-This project is released under the MIT license, while InternLM is licensed under the Apache-2.0 license.
+This project is released under the MIT license, while InternLM2 is licensed under the Apache-2.0 license.
 
 ## Citation