docs(readme): update changelog and compatibility information

- Update changelog for version 1.3.0 release
- Clarify CUDA and GPU compatibility improvements
- Add information about batch processing speed improvements
- Update model download process and memory usage optimizations
- Include link to batch processing demo script

README.md

@@ -49,14 +49,14 @@ Easier to use: Just grab MinerU Desktop. No coding, no login, just a simple inte
 # Changelog
 - 2025/04/03 Release of version 1.3.0, with many changes in this version:
   - Installation and compatibility optimization
-    - By using paddleocr2torch, completely replaced the paddle framework and paddleocr used in the project, resolving conflicts between paddle and torch (OCR speed under single-process is slightly slower compared to the paddle framework).
+    - By using paddleocr2torch, completely replaced the paddle framework and paddleocr used in the project, resolving conflicts between paddle and torch.
     - Removed the use of layoutlmv3 in layout, solving compatibility issues caused by `detectron2`.
     - Extended torch version compatibility to 2.2~2.6.
-    - CUDA compatibility extended to 11.8~12.6 (CUDA version determined by torch), addressing compatibility issues for some users with 50-series and H-series GPUs.
+    - CUDA compatibility extended to 11.8~12.6 (CUDA version determined by torch), addressing compatibility issues for some users with 50-series and H-series Nvidia GPUs.
     - Python compatible versions extended to 3.10~3.12, resolving the issue of automatic downgrade to 0.6.1 during installation in non-3.10 environments.
   - Performance optimization (compared to version 1.0.1, formula parsing speed improved by over 1400%, and overall parsing speed improved by over 500%)
-    - Supported batch processing for multiple PDF files, enhancing the parsing speed of batch files.
-    - Optimized the loading and usage of the mfr model, reducing memory usage and improving parsing speed.
+    - Improved parsing speed for batch processing of multiple small PDF files ([script example](demo/batch_demo.py)).
+    - Optimized the loading and usage of the mfr model, reducing memory usage and improving parsing speed. (requires re-executing the [model download process](docs/how_to_download_models_en.md) to obtain incremental updates of model files)
     - Optimized memory usage, allowing the project to run with as little as 6GB.
     - Improved running speed on mps devices.
   - Parsing effect optimization

README_zh-CN.md

@@ -48,14 +48,15 @@
 # 更新记录
 - 2025/04/03 1.3.0 发布，在这个版本我们做出了许多改变：
   - 安装与兼容性优化
-    - 通过使用paddleocr2torch，完全替代了paddle框架以及paddleocr在项目中的使用，解决了paddle和torch的冲突问题（单进程下ocr速度相比paddle框架略有小幅下降）
+    - 通过使用paddleocr2torch，完全替代了paddle框架以及paddleocr在项目中的使用，解决了paddle和torch的冲突问题
     - 通过移除layout中layoutlmv3的使用，解决了由`detectron2`导致的兼容问题
     - torch版本兼容扩展到2.2~2.6
     - cuda兼容扩展到11.8~12.6（cuda版本由torch决定），解决部分用户50系显卡与H系显卡的兼容问题
     - python兼容版本扩展到3.10~3.12，解决了在非3.10环境下安装时自动降级到0.6.1的问题
+    - 优化离线部署流程，部署成功后不需要联网下载任何模型文件
   - 性能优化（与1.0.1版本相比，公式解析速度最高提升超过1400%，整体解析速度提升超过500%）
-    - 通过支持多个pdf文件的batch，提升了批量文件的解析速度 
-    - 通过优化mfr模型的加载和使用，降低了显存占用并提升了解析速度
+    - 通过支持多个pdf文件的batch处理（[脚本样例](demo/batch_demo.py)），提升了批量小文件的解析速度
+    - 通过优化mfr模型的加载和使用，降低了显存占用并提升了解析速度(需重新执行[模型下载流程](docs/how_to_download_models_zh_cn.md)以获得模型文件的增量更新)
     - 优化显存占用，最低仅需6GB即可运行本项目
     - 优化了在mps设备上的运行速度
   - 解析效果优化