From 1894c26d6f58830c82833aaec50dbb0d90c450cc Mon Sep 17 00:00:00 2001 From: JessyTsu1 <51992423+JessyTsu1@users.noreply.github.com> Date: Thu, 11 Jan 2024 23:10:55 +0800 Subject: [PATCH] Update README.md --- README.md | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/README.md b/README.md index 0036c7d..a4ead9a 100644 --- a/README.md +++ b/README.md @@ -151,15 +151,15 @@ These visual representations offer a glimpse into the diverse world of personali ## ❤️ Acknowledgments -[LLaMA-Efficient-Tuning](https://github.com/hiyouga/LLaMA-Factory/): A standardized LLM end-to-end training solution. +- **[LLaMA-Efficient-Tuning](https://github.com/hiyouga/LLaMA-Factory/)**: A standardized LLM end-to-end training solution. -[魔搭ModelScope](https://modelscope.cn/studios/FarReelAILab/Machine_Mindset): Special thanks to Professor ChengChen for tirelessly working overtime to migrate all models for us and debug the model running demos. 🌟 +- **[魔搭ModelScope](https://modelscope.cn/studios/FarReelAILab/Machine_Mindset)**: Special thanks to Professor ChengChen for tirelessly working overtime to migrate all models for us and debug the model running demos. 🌟 -[HuggingFace](https://huggingface.co/spaces/FarReelAILab/Machine_Mindset): We appreciate their model hosting and community support. 👏 +- **[HuggingFace](https://huggingface.co/spaces/FarReelAILab/Machine_Mindset)**: We appreciate their model hosting and community support. 👏 -[OpenXLab](https://openxlab.org.cn/usercenter/FarReelAILab?vtab=create&module=models): Thanks to their inference computing power and community support. 💪 +- **[OpenXLab](https://openxlab.org.cn/usercenter/FarReelAILab?vtab=create&module=models)**: Thanks to their inference computing power and community support. 💪 -[ChatLaw](https://github.com/PKU-YuanGroup/ChatLaw)： Gratitude to the ChatLaw team for providing efficient and clean data processing approaches, as well as their rich engineering expertise. 🙏 +- **[ChatLaw](https://github.com/PKU-YuanGroup/ChatLaw)**： Gratitude to the ChatLaw team for providing efficient and clean data processing approaches, as well as their rich engineering expertise. 🙏