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@@ -4,7 +4,7 @@ language:
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  - en
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  ---
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  # **Introduction**
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- MoMo-70B-lora-1.8.7-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.
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  [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.
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  Note that we did not exploit any form of weight merge.
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  For leaderboard submission, the trained weight is realigned for compatibility with llama.
@@ -25,7 +25,7 @@ MoMo-70B is trained using **[Moreh](https://moreh.io/)**'s [MoAI platform](https
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  | Model | ARC | MMLU | TruthfulQA | GSM8K |
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  |------------------------------|-------|-------|-------|-------|
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- | **V1.8.6(result < 0.1, %)**| TBU |TBU | TBU | TBU |
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  ### Used Environments
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  - AMD MI250 & MoAI platform
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  - Please visit https://moreh.io/product for more information about MoAI platform
@@ -38,8 +38,8 @@ MoMo-70B is trained using **[Moreh](https://moreh.io/)**'s [MoAI platform](https
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  import torch
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  from transformers import AutoModelForCausalLM, AutoTokenizer
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- tokenizer = AutoTokenizer.from_pretrained("moreh/MoMo-70B-lora-1.8.7-DPO")
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  model = AutoModelForCausalLM.from_pretrained(
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- "moreh/MoMo-70B-lora-1.8.6-DPO"
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  )
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  ```
 
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  - en
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  ---
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  # **Introduction**
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+ MoMo-72B-lora-1.8.7-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.
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  [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.
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  Note that we did not exploit any form of weight merge.
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  For leaderboard submission, the trained weight is realigned for compatibility with llama.
 
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  | Model | ARC | MMLU | TruthfulQA | GSM8K |
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  |------------------------------|-------|-------|-------|-------|
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+ | **V1.8.7(result < 0.1, %)**| TBU |TBU | TBU | TBU |
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  ### Used Environments
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  - AMD MI250 & MoAI platform
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  - Please visit https://moreh.io/product for more information about MoAI platform
 
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  import torch
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  from transformers import AutoModelForCausalLM, AutoTokenizer
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+ tokenizer = AutoTokenizer.from_pretrained("moreh/MoMo-72B-lora-1.8.7-DPO")
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  model = AutoModelForCausalLM.from_pretrained(
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+ "moreh/MoMo-72B-lora-1.8.7-DPO"
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  )
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  ```