diff --git a/README.md b/README.md
index 64e3769..3343b57 100644
--- a/README.md
+++ b/README.md
@@ -69,7 +69,7 @@ InternLM2 series are released with the following features:
 The release of InternLM2 series contains two model sizes: 7B and 20B. 7B models are efficient for research and application and 20B models are more powerful and can support more complex scenarios. For each model size, there are four types of models for different user requirements
 
 1. InternLM2-Base: Foundation models with high quality and high adaptation flexibility, which serve as a good starting point for downstream deep adaptations.
-2. InternLM2: Optimized in multiple dimensions based on InternLM2-Base, obtaining state-of-the-art performance in evaluation with good language capability. InternLM2 models are recommended for consideration in most applications.
+2. InternLM2: Further pretrain with general domain data and domain-enhanced corpus, obtaining state-of-the-art performance in evaluation with good language capability. InternLM2 models are recommended for consideration in most applications.
 3. InternLM2-Chat-SFT: Intermediate version of InternLM2-Chat that only undergoes supervised fine-tuning (SFT), based on the InternLM2-Base model. We release them to benefit research on alignment.
 4. InternLM2-Chat: Further aligned on top of InternLM2-Chat-SFT through online RLHF. InternLM2-Chat exhibits better instruction following, chat experience, and function call, which is recommended for downstream applications.
 
diff --git a/README_zh-CN.md b/README_zh-CN.md
index 2125219..0b24a7f 100644
--- a/README_zh-CN.md
+++ b/README_zh-CN.md
@@ -67,7 +67,7 @@ InternLM2 系列模型在本仓库正式发布，具有如下特性：
 在此次发布中，InternLM2 包含两种模型规格：7B 和 20B。7B 为轻量级的研究和应用提供了一个轻便但性能不俗的模型，20B 模型的综合性能更为强劲，可以有效支持更加复杂的实用场景。面向不同的使用需求，每个规格包含四个模型版本：
 
 1. InternLM2-Base：高质量和具有很强可塑性的模型基座，是模型进行深度领域适配的高质量起点。
-2. InternLM2：在 Base 模型基础上，在多个能力方向进行了强化，在评测中成绩优异，同时保持了很好的通用语言能力，是我们推荐的在大部分应用中考虑选用的优秀基座。
+2. InternLM2：进一步在大规模无标签数据上进行预训练，并结合特定领域的增强语料库进行训练，在评测中成绩优异，同时保持了很好的通用语言能力，是我们推荐的在大部分应用中考虑选用的优秀基座。
 3. InternLM2-Chat-SFT: 基于 InternLM2-Base 模型进行了有监督微调，是 InternLM2-Chat 模型的中间版本。我们将它们开源以助力社区在对齐方面的研究。
 4. InternLM2-Chat: 在 InternLM2-Chat-SFT 的基础上进行了 online RLHF 以进一步对齐. InternLM2-Chat 面向对话交互进行了优化，具有较好的指令遵循、共情聊天和调用工具等的能力，是我们推荐直接用于下游应用的模型。
 
diff --git a/model_cards/internlm2_20b.md b/model_cards/internlm2_20b.md
index 640c852..1ac71c2 100644
--- a/model_cards/internlm2_20b.md
+++ b/model_cards/internlm2_20b.md
@@ -5,7 +5,7 @@
 The second generation of the InternLM model, InternLM2, includes models at two scales: 7B and 20B. For the convenience of users and researchers, we have open-sourced four versions of each scale of the model, which are:
 
 - internlm2-base-20b: Foundation models with high quality and high adaptation flexibility, which serve as a good starting point for downstream deep adaptations.
-- internlm2-20b (**recommended**): Optimized in multiple dimensions based on InternLM2-Base, obtaining state-of-the-art performance in evaluation with good language capability. InternLM2 models are recommended for consideration in most applications.
+- internlm2-20b (**recommended**): Further pretrain with general domain data and domain-enhanced corpus, obtaining state-of-the-art performance in evaluation with good language capability. InternLM2 models are recommended for consideration in most applications.
 - internlm2-chat-20b-sft: Intermediate version of InternLM2-Chat that only undergoes supervised fine-tuning (SFT), based on the InternLM2-Base model. We release them to benefit research on alignment.
 - internlm2-chat-20b (**recommended**): Further aligned on top of InternLM2-Chat-SFT through online RLHF. InternLM2-Chat exhibits better instruction following, chat experience, and function calling, which is recommended for downstream applications.
 
diff --git a/model_cards/internlm2_7b.md b/model_cards/internlm2_7b.md
index 950a607..e663e75 100644
--- a/model_cards/internlm2_7b.md
+++ b/model_cards/internlm2_7b.md
@@ -5,7 +5,7 @@
 The second generation of the InternLM model, InternLM2, includes models at two scales: 7B and 20B. For the convenience of users and researchers, we have open-sourced four versions of each scale of the model, which are:
 
 - internlm2-base-7b: Foundation models with high quality and high adaptation flexibility, which serve as a good starting point for downstream deep adaptations.
-- internlm2-7b (**recommended**): Optimized in multiple dimensions based on InternLM2-Base, obtaining state-of-the-art performance in evaluation with good language capability. InternLM2 models are recommended for consideration in most applications.
+- internlm2-7b (**recommended**): Further pretrain with general domain data and domain-enhanced corpus, obtaining state-of-the-art performance in evaluation with good language capability. InternLM2 models are recommended for consideration in most applications.
 - internlm2-chat-7b-sft: Intermediate version of InternLM2-Chat that only undergoes supervised fine-tuning (SFT), based on the InternLM2-Base model. We release them to benefit research on alignment.
 - internlm2-chat-7b (**recommended**): Further aligned on top of InternLM2-Chat-SFT through online RLHF. InternLM2-Chat exhibits better instruction following, chat experience, and function calling, which is recommended for downstream applications.