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README.md

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 # **Introduction**
-MoMo-70B is trained via Supervised Fine-Tuning (SFT) using [LoRA](https://arxiv.org/abs/2106.09685), with the QWEN-72B model as its base-model.  
-This is a Direct Preference Optimization([DPO](https://arxiv.org/abs/2305.18290)) version of v1.4  
+MoMo-70B-lora-1.8.4-DPO is trained via Direct Preference Optimization([DPO](https://arxiv.org/abs/2305.18290)) from [MoMo-70B-LoRA-V1.4](https://huggingface.co/moreh/MoMo-70B-LoRA-V1.4) as its base model, with several optimizations in hyperparameters.  
+[MoMo-70B-LoRA-V1.4](https://huggingface.co/moreh/MoMo-70B-LoRA-V1.4) is trained via Supervised Fine-Tuning (SFT) using [LoRA](https://arxiv.org/abs/2106.09685), with the QWEN-72B model as its base-model.  
 Note that we did not exploit any form of weight merge.  
 For leaderboard submission, the trained weight is realigned for compatibility with llama.  
 MoMo-70B is trained using **[Moreh](https://moreh.io/)**'s [MoAI platform](https://moreh.io/product), which simplifies the training of large-scale models, and AMD's MI250 GPU.