text2model-v3 (#111)

Author: YalinFeng01

docs/en/notes/guide/pipelines/Text2ModelPipeline.md

@@ -91,9 +91,7 @@ After initialization, the project directory becomes:
 
 ```
 Project Root/
-├── sft_data_pipeline.py      # Pipeline execution file
 ├── text_2_qa_pipeline.py     # Text2QA generation pipeline
-├── merge_filter_qa_pairs.py  # QA format conversion script
 └── .cache/                   # Cache directory
     └── train_config.yaml     # Default configuration file for llamafactory training
 ```
@@ -114,9 +112,7 @@ After fine-tuning completion, the project directory becomes:
 
 ```
 Project Root/
-├── sft_data_pipeline.py      # Pipeline execution file
-├── text_2_qa_pipeline.py     # Text2QA generation pipeline
-├── merge_filter_qa_pairs.py  # QA format conversion script
+├── text_2_qa_pipeline.py     # Text2QA generation
 └── .cache/                   # Cache directory
     ├── train_config.yaml     # Default configuration file for llamafactory training
     ├── pt_input.jsonl        # Merged input data
@@ -139,10 +135,10 @@ Project Root/
 
 ```bash
 # Method 1: Specify model path with --model flag (optional)
-# Default path: .cache/saves/pdf2model_cache_{timestamp}
+# Default path: .cache/saves/text2model_cache_{timestamp}
 dataflow chat --model ./custom_model_path
 
 # Method 2: Navigate to model directory and run dataflow chat
-cd .cache/saves/pdf2model_cache_{timestamp}
+cd .cache/saves/text2model_cache_{timestamp}
 dataflow chat
 ```

docs/zh/notes/guide/pipelines/Text2ModelPipeline.md

@@ -3,7 +3,7 @@ title: Text2ModelPipeline
 createTime: 2025/08/31 03:42:26
 permalink: /zh/guide/ndyvouo2/
 ---
-# DataFlow-pdf2model&LlaMA-Factory
+# DataFlow-text2model&LlaMA-Factory
 
 ## 快速开始
 
@@ -76,20 +76,20 @@ cd run_dataflow
 
 
 
-## 第四步: 初始化dataflow-pdf2model
+## 第四步: 初始化dataflow-text2model
 
 ```
 #初始化 
 #--cache 可以指定.cache目录的位置（可选）
 #默认值为当前文件夹目录
-dataflow pdf2model init
+dataflow text2model init
 ```
 
 初始化完成后，项目目录变成：
 
 ```shell
 项目根目录/
-├── sft_data_pipeline.py  # pipeline执行文件
+├── text_to_qa_pipeline.py  # pipeline执行文件
 └── .cache/            # 缓存目录
     └── train_config.yaml  # llamafactory训练的默认配置文件
 ```
@@ -110,7 +110,7 @@ dataflow text2model train
 
 ```
 项目根目录/
-├── sft_data_pipeline.py  # pipeline执行文件
+├── text_to_qa_pipeline.py  # pipeline执行文件
 └── .cache/            # 缓存目录
     ├── train_config.yaml  # llamafactory训练的默认配置文件
     ├── data/
@@ -134,7 +134,7 @@ dataflow text2model train
 
 ```
 #用法一:--model 可以指定 对话模型的路径位置（可选）
-#默认值为.cache/saves/pdf2model_cache_{timestamp}
+#默认值为.cache/saves/text2model_cache_{timestamp}
 #用法二:到模型文件夹下 运行dataflow chat
 dataflow chat --model ./custom_model_path
 ```