[Docs] update chat readme

chat/README.md

@@ -2,13 +2,13 @@
 
 English | [简体中文](./README_zh-CN.md)
 
-This document briefly shows how to use [Transformers](#import-from-transformers), [ModelScope](#import-from-modelscope), and [Web demos](#dialogue) to conduct inference with InternLM2-Chat.
+This document briefly shows how to use [Transformers](#import-from-transformers), [ModelScope](#import-from-modelscope), and [Web demos](#dialogue) to conduct inference with InternLM2.5-Chat.
 
 You can also know more about the [chatml format](./chat_format.md) and how to use [LMDeploy for inference and model serving](./lmdeploy.md).
 
 ## Import from Transformers
 
-To load the InternLM2 7B Chat model using Transformers, use the following code:
+To load the InternLM2.5 7B Chat model using Transformers, use the following code:
 
 ```python
 >>> from transformers import AutoTokenizer, AutoModelForCausalLM
@@ -31,7 +31,7 @@ Remember, good time management skills take practice and patience. Start with sma
 
 ## Import from ModelScope
 
-To load the InternLM model using ModelScope, use the following code:
+To load the InternLM2.5 Chat model using ModelScope, use the following code:
 
 ```python
 from modelscope import snapshot_download, AutoTokenizer, AutoModelForCausalLM
@@ -48,7 +48,7 @@ print(response)
 
 ## Dialogue
 
-You can interact with the InternLM Chat 7B model through a frontend interface by running the following code:
+You can interact with the InternLM2.5 Chat model through a frontend interface by running the following code:
 
 ```bash
 pip install streamlit

chat/README_zh-CN.md

@@ -3,9 +3,9 @@
 [English](./README.md) | 简体中文
 
 本文介绍采用 [Transformers](#import-from-transformers)、[ModelScope](#import-from-modelscope)、[Web demos](#dialogue)
-对 InternLM2-Chat 进行推理。
+对 InternLM2.5-Chat 进行推理。
 
-你还可以进一步了解 InternLM2-Chat 采用的[对话格式](./chat_format_zh-CN.md)，以及如何[用 LMDeploy 进行推理或部署服务](./lmdeploy_zh-CN.md)，或者尝试用 [OpenAOE](./openaoe.md) 与多个模型对话。
+你还可以进一步了解 InternLM2.5-Chat 采用的[对话格式](./chat_format_zh-CN.md)，以及如何[用 LMDeploy 进行推理或部署服务](./lmdeploy_zh-CN.md)，或者尝试用 [OpenAOE](./openaoe.md) 与多个模型对话。
 
 ## 通过 Transformers 加载
 
@@ -25,7 +25,7 @@
 
 ### 通过 ModelScope 加载
 
-通过以下的代码从 ModelScope 加载 InternLM2-Chat 模型 （可修改模型名称替换不同的模型）
+通过以下的代码从 ModelScope 加载 InternLM2.5-Chat 模型 （可修改模型名称替换不同的模型）
 
 ```python
 from modelscope import snapshot_download, AutoTokenizer, AutoModelForCausalLM
@@ -42,7 +42,7 @@ print(response)
 
 ## 通过前端网页对话
 
-可以通过以下代码启动一个前端的界面来与 InternLM2 Chat 7B 模型进行交互
+可以通过以下代码启动一个前端的界面来与 InternLM2.5 Chat 7B 模型进行交互
 
 ```bash
 pip install streamlit

chat/chat_format.md

@@ -17,7 +17,7 @@ Hello<|im_end|>
 Hello, I am InternLM2-Chat, how can I assist you?<|im_end|>
 ```
 
-Here, `<|im_start|>` acts as the start token for each turn of dialogue, and `<|im_end|>` as the end token. Each turn of dialogue typically starts with `<|im_start|>role` and ends with the model's output `<|im_end|>`, where role represents `system`, `user`, `assistant`, and `environment`. You may refer to the [code in huggingface](https://huggingface.co/internlm/internlm2_5-7b-chat/blob/main/modeling_internlm2.py#L1138) to see how the chat history is organized.
+Here, `<|im_start|>` acts as the start token for each turn of dialogue, and `<|im_end|>` as the end token. Each turn of dialogue typically starts with `<|im_start|>role` and ends with the model's output `<|im_end|>`, where role represents `system`, `user`, `assistant`, and `environment`. You may refer to the [code in huggingface](https://huggingface.co/internlm/internlm2_5-7b-chat/blob/main/modeling_internlm2.py#L1357) to see how the chat history is organized.
 
 Currently, the InternLM2-Chat model's vocabulary maintains the following mappings to support full functionalities:
 

chat/chat_format_zh-CN.md

@@ -17,7 +17,7 @@ InternLM2-Chat 采用了全新的对话格式，以灵活地支持工具调用
 你好，我是书生浦语，请问有什么可以帮助你的吗<|im_end|>
 ```
 
-其中 `<|im_start|>` 充当了每轮对话开始符，`<|im_end|>` 充当了当前轮对话结束符。每轮对话一般以 `<|im_start|>role` 开头，以模型输出的 `<|im_end|>` 结尾，role 代表 `system`，`user`，`assistant` 和 `environment` 角色。你可以参考[huggingface 上的代码](https://huggingface.co/internlm/internlm2_5-7b-chat/blob/main/modeling_internlm2.py#L1138)来了解对话历史的拼接。
+其中 `<|im_start|>` 充当了每轮对话开始符，`<|im_end|>` 充当了当前轮对话结束符。每轮对话一般以 `<|im_start|>role` 开头，以模型输出的 `<|im_end|>` 结尾，role 代表 `system`，`user`，`assistant` 和 `environment` 角色。你可以参考[huggingface 上的代码](https://huggingface.co/internlm/internlm2_5-7b-chat/blob/main/modeling_internlm2.py#L1357)来了解对话历史的拼接。
 
 目前，InternLM2-Chat 模型的词表中还维护了如下映射