modelscope · yxdyc · Oct 11, 2023 · Oct 11, 2023 · Oct 11, 2023 · Oct 11, 2023
diff --git a/README.md b/README.md
@@ -52,7 +52,7 @@ Table of Contents
 
 ## Features
 
-![Overview](https://img.alicdn.com/imgextra/i4/O1CN01uvLL0T1VIaX28dMLg_!!6000000002630-2-tps-2509-1192.png)
+![Overview](https://img.alicdn.com/imgextra/i2/O1CN01IMPeD11xYRUYLmXKO_!!6000000006455-2-tps-3620-1604.png)
 
 - **Systematic & Reusable**: 
   Empowering users with a systematic library of 20+ reusable [config recipes](configs), 50+ core [OPs](docs/Operators.md), and feature-rich 
@@ -64,8 +64,7 @@ Table of Contents
   ![Data-in-the-loop](https://img.alicdn.com/imgextra/i1/O1CN011E99C01ndLZ55iCUS_!!6000000005112-0-tps-2701-1050.jpg)
 
 - **Comprehensive Data Processing Recipes**: Offering tens of [pre-built data 
-  processing recipes](configs/data_juicer_recipes/README.md) for 
-  pre-training, post-tuning, en, zh, and more scenarios. Validated on 
+  processing recipes](configs/data_juicer_recipes/README.md) for pre-training, fine-tuning, en, zh, and more scenarios. Validated on 
   reference LLaMA models.  
   ![exp_llama](https://img.alicdn.com/imgextra/i1/O1CN01D0Nuof1uOPxvBVEq9_!!6000000006027-0-tps-2324-754.jpg)
 
@@ -124,11 +123,18 @@ pip install py-data-juicer
 
 ### Using Docker
 
-- Run the following command to build the docker image including the latest `data-juicer` with provided [Dockerfile](Dockerfile):
+- You can 
+  - either pull our pre-built image from DockerHub:
+    ```shell
+    docker pull datajuicer/data-juicer:<version_tag>
+    ```
 
-```shell
-docker build -t data-juicer:<version_tag> .
-```
+  - or run the following command to build the docker image including the 
+    latest `data-juicer` with provided [Dockerfile](Dockerfile):
+
+    ```shell
+    docker build -t data-juicer:<version_tag> .
+    ```
 
 ### Installation check
 
@@ -271,7 +277,7 @@ docker exec -it <container_id> bash
 - [Recipes for data process in BLOOM](configs/reproduced_bloom/README.md)
 - [Recipes for data process in RedPajama](configs/redpajama/README.md)
 - [Refined recipes for pre-training data](configs/data_juicer_recipes/README.md)
-- [Refined recipes for post-tuning data](configs/data_juicer_recipes/README.md#before-and-after-refining-for-alpaca-cot-dataset)
+- [Refined recipes for fine-tuning data](configs/data_juicer_recipes/README.md#before-and-after-refining-for-alpaca-cot-dataset)
 
 ## Demos
 - Introduction to Data-Juicer [[ModelScope](https://modelscope.cn/studios/Data-Juicer/overview_scan/summary)]

diff --git a/README_ZH.md b/README_ZH.md
@@ -51,13 +51,13 @@ Data-Juicer 是一个一站式数据处理系统，旨在为大语言模型 (LLM
 
 ## 特点
 
-![Overview](https://img.alicdn.com/imgextra/i4/O1CN01uvLL0T1VIaX28dMLg_!!6000000002630-2-tps-2509-1192.png)
+![Overview](https://img.alicdn.com/imgextra/i2/O1CN01IMPeD11xYRUYLmXKO_!!6000000006455-2-tps-3620-1604.png)
 
 * **系统化 & 可复用**：为用户提供系统化且可复用的20+[配置菜谱](configs/README_ZH.md)，50+核心[算子](docs/Operators_ZH.md)和专用[工具池](#documentation)，旨在让数据处理独立于特定的大语言模型数据集和处理流水线。
 
 * **数据反馈回路**：支持详细的数据分析，并提供自动报告生成功能，使您深入了解您的数据集。结合多维度自动评估功能，支持在 LLM 开发过程的多个阶段进行及时反馈循环。  ![Data-in-the-loop](https://img.alicdn.com/imgextra/i1/O1CN011E99C01ndLZ55iCUS_!!6000000005112-0-tps-2701-1050.jpg)
 
-* **全面的数据处理菜谱**：为pre-training、post-tuning、中英文等场景提供数十种[预构建的数据处理菜谱](configs/data_juicer_recipes/README_ZH.md)。  ![exp_llama](https://img.alicdn.com/imgextra/i1/O1CN01D0Nuof1uOPxvBVEq9_!!6000000006027-0-tps-2324-754.jpg)
+* **全面的数据处理菜谱**：为pre-training、fine-tuning、中英文等场景提供数十种[预构建的数据处理菜谱](configs/data_juicer_recipes/README_ZH.md)。  ![exp_llama](https://img.alicdn.com/imgextra/i1/O1CN01D0Nuof1uOPxvBVEq9_!!6000000006027-0-tps-2324-754.jpg)
 
 * **效率增强**：提供高效的数据处理流水线，减少内存占用和CPU开销，提高生产力。  ![sys-perf](https://img.alicdn.com/imgextra/i4/O1CN01Sk0q2U1hdRxbnQXFg_!!6000000004300-0-tps-2438-709.jpg)
 
@@ -112,11 +112,16 @@ pip install py-data-juicer
 
 ### 使用 Docker 安装
 
-- 运行如下命令用我们提供的 [Dockerfile](Dockerfile) 来构建包括最新版本的 `data-juicer` 的 docker 镜像：
+- 您可以选择
+  - 从DockerHub直接拉取我们的预置镜像:
+    ```shell
+    docker pull datajuicer/data-juicer:<version_tag>
+    ```
+  - 或者运行如下命令用我们提供的 [Dockerfile](Dockerfile) 来构建包括最新版本的 `data-juicer` 的 docker 镜像：
 
-```shell
-docker build -t data-juicer:<version_tag> .
-```
+    ```shell
+    docker build -t data-juicer:<version_tag> .
+    ```
 
 ### 安装校验
 
@@ -253,7 +258,7 @@ docker exec -it <container_id> bash
 * [BLOOM 数据处理菜谱](configs/reproduced_bloom/README_ZH.md)
 * [RedPajama 数据处理菜谱](configs/reproduced_redpajama/README_ZH.md)
 * [预训练数据增强菜谱](configs/data_juicer_recipes/README_ZH.md)
-* [Post-tuning数据增强菜谱](configs/data_juicer_recipes/README_ZH.md#完善前后的alpaca-cot数据集)
+* [Fine-tuning数据增强菜谱](configs/data_juicer_recipes/README_ZH.md#完善前后的alpaca-cot数据集)
 
 ## 演示样例
 

diff --git a/app.py b/app.py
@@ -423,7 +423,7 @@ def set_sliders(total_stats, ordered):
 
     @staticmethod
     def diversity():
-        with st.expander('Diversity for sft dataset', expanded=False):
+        with st.expander('Diversity for CFT dataset', expanded=False):
             dataset = st.session_state.get('dataset', None)
             cfg = st.session_state.get('cfg', parse_cfg()[2])
             text_key = st.session_state.get('text_key', 'text')

diff --git a/configs/README.md b/configs/README.md
@@ -29,4 +29,4 @@ We have reproduced the processing flow of some RedPajama datasets. Please refer
 We have reproduced the processing flow of some BLOOM datasets. please refer to the [reproduced_bloom](reproduced_bloom) folder for details.
 
 ### Data-Juicer Recipes
-We have refined some open source datasets (including SFT datasets) by using Data-Juicer and have provided configuration files for the refined flow. please refer to the [data_juicer_recipes](data_juicer_recipes) folder for details.
+We have refined some open source datasets (including CFT datasets) by using Data-Juicer and have provided configuration files for the refined flow. please refer to the [data_juicer_recipes](data_juicer_recipes) folder for details.
diff --git a/configs/README_ZH.md b/configs/README_ZH.md
@@ -30,4 +30,4 @@ Demo 配置文件用于帮助用户快速熟悉 Data-Juicer 的基本功能，
 我们已经重现了部分 BLOOM 数据集的处理流程，请参阅 [reproduced_bloom](reproduced_bloom) 文件夹以获取详细说明。
 
 ### Data-Juicer 菜谱
-我们使用 Data-Juicer 更细致地处理了一些开源数据集（包含 SFT 数据集），并提供了处理流程的配置文件。请参阅 [data_juicer_recipes](data_juicer_recipes) 文件夹以获取详细说明。
+我们使用 Data-Juicer 更细致地处理了一些开源数据集（包含 CFT 数据集），并提供了处理流程的配置文件。请参阅 [data_juicer_recipes](data_juicer_recipes) 文件夹以获取详细说明。
diff --git a/configs/data_juicer_recipes/README.md b/configs/data_juicer_recipes/README.md
@@ -33,5 +33,5 @@ We use simple 3-σ rule to set the hyperparameters for ops in each recipe.
 
 | subset | #samples before     |             #samples after             | keep ratio | config link                                                                                                                                                                                                                        | data link                                                                                                                                                         | source                 |
 |------------------|:-------------------------:|:--------------------------------------:|:----------:|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------|-------------------------|
-| Alpaca-Cot EN | 136,219,879               | 72,855,345 |   54.48%   | [alpaca-cot-en-refine.yaml](alpaca_cot/alpaca-cot-en-refine.yaml)                                                                                                                                                                         | [Aliyun](https://dail-wlcb.oss-cn-wulanchabu.aliyuncs.com/LLM_data/our_refined_datasets/SFT/alpaca-cot-en-refine_result.jsonl) <br> [ModelScope](https://modelscope.cn/datasets/Data-Juicer/alpaca-cot-en-refined-by-data-juicer/summary)                           | [39 Subsets of Alpaca-CoT](alpaca_cot/README.md#refined-alpaca-cot-dataset-meta-info)              |
-| Alpaca-Cot ZH | 21,197,246               |               9,873,214                |   46.58%   | [alpaca-cot-zh-refine.yaml](alpaca_cot/alpaca-cot-zh-refine.yaml)                                                                                                                                                                         | [Aliyun](https://dail-wlcb.oss-cn-wulanchabu.aliyuncs.com/LLM_data/our_refined_datasets/SFT/alpaca-cot-zh-refine_result.jsonl) <br> [ModelScope](https://modelscope.cn/datasets/Data-Juicer/alpaca-cot-zh-refined-by-data-juicer/summary)                           | [28 Subsets of Alpaca-CoT](alpaca_cot/README.md#refined-alpaca-cot-dataset-meta-info)              |
+| Alpaca-Cot EN | 136,219,879               | 72,855,345 |   54.48%   | [alpaca-cot-en-refine.yaml](alpaca_cot/alpaca-cot-en-refine.yaml)                                                                                                                                                                         | [Aliyun](https://dail-wlcb.oss-cn-wulanchabu.aliyuncs.com/LLM_data/our_refined_datasets/CFT/alpaca-cot-en-refine_result.jsonl) <br> [ModelScope](https://modelscope.cn/datasets/Data-Juicer/alpaca-cot-en-refined-by-data-juicer/summary)                           | [39 Subsets of Alpaca-CoT](alpaca_cot/README.md#refined-alpaca-cot-dataset-meta-info)              |
+| Alpaca-Cot ZH | 21,197,246               |               9,873,214                |   46.58%   | [alpaca-cot-zh-refine.yaml](alpaca_cot/alpaca-cot-zh-refine.yaml)                                                                                                                                                                         | [Aliyun](https://dail-wlcb.oss-cn-wulanchabu.aliyuncs.com/LLM_data/our_refined_datasets/CFT/alpaca-cot-zh-refine_result.jsonl) <br> [ModelScope](https://modelscope.cn/datasets/Data-Juicer/alpaca-cot-zh-refined-by-data-juicer/summary)                           | [28 Subsets of Alpaca-CoT](alpaca_cot/README.md#refined-alpaca-cot-dataset-meta-info)              |
diff --git a/configs/data_juicer_recipes/README_ZH.md b/configs/data_juicer_recipes/README_ZH.md
@@ -33,5 +33,5 @@
 
 | 数据子集              |         完善前的样本数目         |              完善后的样本数目              |   样本保留率   | 配置链接                                                                                                                                                                                                                                | 数据链接                                                                                                                                                                                                                                     | 来源                                            |
 |-------------------|:------------------------:|:----------------------------------:|:---------:|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------|
-| Alpaca-Cot EN     |       136,219,879        | 72,855,345 |   54.48%   | [alpaca-cot-en-refine.yaml](alpaca_cot/alpaca-cot-en-refine.yaml)                                                                                                                                                                   | [Aliyun](https://dail-wlcb.oss-cn-wulanchabu.aliyuncs.com/LLM_data/our_refined_datasets/SFT/alpaca-cot-en-refine_result.jsonl) <br> [ModelScope](https://modelscope.cn/datasets/Data-Juicer/alpaca-cot-en-refined-by-data-juicer/summary) | [来自Alpaca-CoT的39个子集](alpaca_cot/README_ZH.md#完善的-alpaca-cot-数据集元信息) |
-| Alpaca-Cot ZH     |        21,197,246        |             9,873,214              |  46.58%   | [alpaca-cot-zh-refine.yaml](alpaca_cot/alpaca-cot-zh-refine.yaml)                                                                                                                                                                   | [Aliyun](https://dail-wlcb.oss-cn-wulanchabu.aliyuncs.com/LLM_data/our_refined_datasets/SFT/alpaca-cot-zh-refine_result.jsonl) <br> [ModelScope](https://modelscope.cn/datasets/Data-Juicer/alpaca-cot-zh-refined-by-data-juicer/summary) | [来自Alpaca-CoT的28个子集](alpaca_cot/README_ZH.md#完善的-alpaca-cot-数据集元信息) |
+| Alpaca-Cot EN     |       136,219,879        | 72,855,345 |   54.48%   | [alpaca-cot-en-refine.yaml](alpaca_cot/alpaca-cot-en-refine.yaml)                                                                                                                                                                   | [Aliyun](https://dail-wlcb.oss-cn-wulanchabu.aliyuncs.com/LLM_data/our_refined_datasets/CFT/alpaca-cot-en-refine_result.jsonl) <br> [ModelScope](https://modelscope.cn/datasets/Data-Juicer/alpaca-cot-en-refined-by-data-juicer/summary) | [来自Alpaca-CoT的39个子集](alpaca_cot/README_ZH.md#完善的-alpaca-cot-数据集元信息) |
+| Alpaca-Cot ZH     |        21,197,246        |             9,873,214              |  46.58%   | [alpaca-cot-zh-refine.yaml](alpaca_cot/alpaca-cot-zh-refine.yaml)                                                                                                                                                                   | [Aliyun](https://dail-wlcb.oss-cn-wulanchabu.aliyuncs.com/LLM_data/our_refined_datasets/CFT/alpaca-cot-zh-refine_result.jsonl) <br> [ModelScope](https://modelscope.cn/datasets/Data-Juicer/alpaca-cot-zh-refined-by-data-juicer/summary) | [来自Alpaca-CoT的28个子集](alpaca_cot/README_ZH.md#完善的-alpaca-cot-数据集元信息) |