Correct the trainer used for DPO

README.md

@@ -7,6 +7,7 @@ model-index:
 - name: yanolja/EEVE-Korean-Instruct-10.8B-v1.0
   results: []
 ---
+[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
 
 <p align="left">
   <img src="https://huggingface.co/yanolja/EEVE-Korean-Instruct-10.8B-v1.0/resolve/main/eeve_logo.webp" width="50%"/>
@@ -28,7 +29,7 @@ If you're passionate about the field of Large Language Models and wish to exchan
 
 ## About the Model
 
-This model is a fine-tuned version of [yanolja/EEVE-Korean-10.8B-v1.0](https://huggingface.co/yanolja/EEVE-Korean-10.8B-v1.0), which is a Korean vocabulary-extended version of [upstage/SOLAR-10.7B-v1.0](https://huggingface.co/upstage/SOLAR-10.7B-v1.0). Specifically, we employed Direct Preference Optimization (DPO) based on [LLaMA-Factory](https://github.com/hiyouga/LLaMA-Factory). 
+This model is a fine-tuned version of [yanolja/EEVE-Korean-10.8B-v1.0](https://huggingface.co/yanolja/EEVE-Korean-10.8B-v1.0), which is a Korean vocabulary-extended version of [upstage/SOLAR-10.7B-v1.0](https://huggingface.co/upstage/SOLAR-10.7B-v1.0). Specifically, we utilized Direct Preference Optimization (DPO) through the use of [Axolotl](https://github.com/OpenAccess-AI-Collective/axolotl).
 
 ## Prompt Template
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