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README.md

@@ -9,24 +9,24 @@ license_link: LICENSE
 </h1>
 </div>
 
-## 模型介绍
+## Model Introduction
 
-我们很高兴首次发布Index系列模型中的轻量版本：Index-1.9B系列
- 本次开源的Index-1.9B 系列包含以下模型： 
-- Index-1.9B base : 基座模型，具有 19亿 非词嵌入参数量，在2.8T 中英文为主的语料上预训练，多个评测基准上与同级别模型比处于领先。
-- **Index-1.9B pure(本仓库模型)** : 基座模型的对照组，与base具有相同的参数和训练策略，不同之处在于我们严格过滤了该版本语料中所有指令相关的数据，以此来验证指令对benchmark的影响。
-- Index-1.9B chat : 基于index-1.9B base通过SFT和DPO对齐后的对话模型，我们发现由于我们预训练中引入了较多互联网社区语料，聊天的趣味性明显更强。
-- Index-1.9B character : 在SFT和DPO的基础上引入了RAG来实现fewshots角色扮演定制。
+We are excited to announce the release of a lightweight version from the Index series models: the Index-1.9B series.
+ The open-source Index-1.9B series includes the following models:
+- **Index-1.9B base (this repository's model)** : The base model, with 1.9 billion non-embedding parameters, pre-trained on a 2.8T corpus mainly in Chinese and English. It leads in multiple evaluation benchmarks compared to models of the same level. 
+- Index-1.9B pure : A control version of the base model with the same parameters and training strategy, but strictly filtered out all instruction-related data from the corpus to verify the impact of instructions on benchmarks.
+- Index-1.9B chat: A dialogue model aligned with SFT and DPO based on the Index-1.9B base. We found that due to the introduction of a lot of internet community corpus in our pre-training, the model has significantly more interesting chatting capabilities.
+- Index-1.9B character : Introduces RAG on top of SFT and DPO to achieve few-shots role-playing customization.
 
-注意：此为Base模型，仅能续写，以及进一步的训练对齐，不能直接交互。
-- Chat模型详见 [Index-1.9B-Chat](https://huggingface.co/IndexTeam/Index-1.9B-Chat)
-- 角色扮演模型详见 [Index-1.9B-Character](https://huggingface.co/IndexTeam/Index-1.9B-Character)
+**Note: This is the Base model, capable only of continuation and further training alignment, and cannot be directly interacted with.**
+- For the **Chat model**, see [Index-1.9B-Chat](https://huggingface.co/IndexTeam/Index-1.9B-Chat)
+- For the **Role-playing model**, see [Index-1.9B-Character](https://huggingface.co/IndexTeam/Index-1.9B-Character)
 
-更多细节详见我们的[GitHub](https://github.com/bilibili/Index-1.9B)和[Index-1.9B技术报告](https://github.com/bilibili/Index-1.9B/blob/main/Index-1.9B%20%E6%8A%80%E6%9C%AF%E6%8A%A5%E5%91%8A.pdf)
+For more details, see our [GitHub](https://github.com/bilibili/Index-1.9B) and [Index-1.9B Technical Report](https://github.com/bilibili/Index-1.9B/blob/main/Index-1.9B%20%E6%8A%80%E6%9C%AF%E6%8A%A5%E5%91%8A.pdf)
 
-## 评测结果
-对通用理解进行评测，Index-1.9B性能优秀，于近期开源的端侧小模型相比领先，并可以和一批7B和大于10B的模型相比较
-|模型|均分|英文均分|MMLU|CEVAL|CMMLU|HellaSwag|Arc-C|Arc-E|
+## Evaluation Results
+The Index-1.9B shows excellent performance in general understanding evaluations, leading compared to recently open-sourced small models and comparable to some 7B and models larger than 10B.
+|Model|Average score|Average English score|MMLU|CEVAL|CMMLU|HellaSwag|Arc-C|Arc-E|
 |----|----|----|----|----|----|----|----|----|
 |Google Gemma 2B|41.58|46.77|41.81|31.36|31.02|66.82|36.39|42.07|
 |Phi-2 (2.7B)|58.89|**72.54**|57.61|31.12|32.05|70.94|74.51|87.1|
@@ -43,5 +43,6 @@ license_link: LICENSE
 |MPT-30B (report)|/|63.48|46.9|/|/|79.9|50.6|76.5|
 |Falcon-40B (report)|/|68.18|55.4|/|/|83.6|54.5|79.2|
 
-评测代码基于[OpenCompass](https://github.com/open-compass/opencompass), 并做了适配性修改，详见[evaluate代码](https://github.com/bilibili/Index-1.9B/evaluate/)
+Evaluation code is based on [OpenCompass](https://github.com/open-compass/opencompass) with compatibility modifications. See the [evaluate](./evaluate/) folder for details.
+
 

README_zh.md

@@ -0,0 +1,47 @@
+---
+license: other
+license_name: license
+license_link: LICENSE
+---
+<div align="center">
+<h1>
+  Index-1.9B
+</h1>
+</div>
+
+## 模型介绍
+
+我们很高兴首次发布Index系列模型中的轻量版本：Index-1.9B系列
+ 本次开源的Index-1.9B 系列包含以下模型： 
+- Index-1.9B base : 基座模型，具有 19亿 非词嵌入参数量，在2.8T 中英文为主的语料上预训练，多个评测基准上与同级别模型比处于领先。
+- **Index-1.9B pure(本仓库模型)** : 基座模型的对照组，与base具有相同的参数和训练策略，不同之处在于我们严格过滤了该版本语料中所有指令相关的数据，以此来验证指令对benchmark的影响。
+- Index-1.9B chat : 基于index-1.9B base通过SFT和DPO对齐后的对话模型，我们发现由于我们预训练中引入了较多互联网社区语料，聊天的趣味性明显更强。
+- Index-1.9B character : 在SFT和DPO的基础上引入了RAG来实现fewshots角色扮演定制。
+
+注意：此为Base模型，仅能续写，以及进一步的训练对齐，不能直接交互。
+- Chat模型详见 [Index-1.9B-Chat](https://huggingface.co/IndexTeam/Index-1.9B-Chat)
+- 角色扮演模型详见 [Index-1.9B-Character](https://huggingface.co/IndexTeam/Index-1.9B-Character)
+
+更多细节详见我们的[GitHub](https://github.com/bilibili/Index-1.9B)和[Index-1.9B技术报告](https://github.com/bilibili/Index-1.9B/blob/main/Index-1.9B%20%E6%8A%80%E6%9C%AF%E6%8A%A5%E5%91%8A.pdf)
+
+## 评测结果
+对通用理解进行评测，Index-1.9B性能优秀，于近期开源的端侧小模型相比领先，并可以和一批7B和大于10B的模型相比较
+|模型|均分|英文均分|MMLU|CEVAL|CMMLU|HellaSwag|Arc-C|Arc-E|
+|----|----|----|----|----|----|----|----|----|
+|Google Gemma 2B|41.58|46.77|41.81|31.36|31.02|66.82|36.39|42.07|
+|Phi-2 (2.7B)|58.89|**72.54**|57.61|31.12|32.05|70.94|74.51|87.1|
+|Qwen1.5-1.8B|58.96|59.28|47.05|59.48|57.12|58.33|56.82|74.93|
+|Qwen2-1.5B(report)|**65.17**|62.52 |56.5|70.6|70.3|66.6|43.9|83.09|
+|MiniCPM-2.4B-SFT|62.53|68.75|53.8|49.19|50.97|67.29|69.44|84.48|
+|**Index-1.9B-Pure**|49.55 |52.83 |43.75|42.35|43.61|63.21|42.75|61.61|
+|**Index-1.9B**|**64.92** |**69.93**|52.53|57.01|52.79|80.69|65.15|81.35|
+|Llama2-7B|50.79|60.31|44.32|32.42|31.11|76|46.3|74.6|
+|Mistral-7B (report) |/|**69.23**|60.1|/|/|81.3|55.5|80|
+|Baichuan2-7B|54.53|53.51|54.64|56.19|56.95|25.04|57.25|77.12|
+|Llama2-13B|57.51|66.61|55.78|39.93|38.7|76.22|58.88|75.56|
+|Baichuan2-13B|68.90|71.69|59.63|59.21|61.27|72.61|70.04|84.48|
+|MPT-30B (report)|/|63.48|46.9|/|/|79.9|50.6|76.5|
+|Falcon-40B (report)|/|68.18|55.4|/|/|83.6|54.5|79.2|
+
+评测代码基于[OpenCompass](https://github.com/open-compass/opencompass), 并做了适配性修改，详见[evaluate代码](https://github.com/bilibili/Index-1.9B/evaluate/)
+