--- language: - en datasets: - Intel/orca_dpo_pairs - argilla/distilabel-math-preference-dpo - kyujinpy/orca_math_dpo pipeline_tag: text-generation license: cc-by-nc-sa-4.0 --- # **Sakura-SOLRCA-Math-Instruct-DPO-v1** ## Model Details **Model Developers** Kyujin Han (kyujinpy) **Method** Using DPO method. With [Intel/orca_dpo_pairs](https://huggingface.co/datasets/Intel/orca_dpo_pairs) and [argilla/distilabel-math-preference-dpo](https://huggingface.co/datasets/argilla/distilabel-math-preference-dpo). I shared the merge version [kyujinpy/orca_math_dpo](https://huggingface.co/datasets/kyujinpy/orca_math_dpo). I will share the information about my model. (training and code) Please see: ⭐[Sakura-SOLAR](https://github.com/KyujinHan/Sakura-SOLAR-DPO). # **Model Benchmark** ## Open leaderboard - Follow up as [link](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). | Model | Average | ARC | HellaSwag | MMLU | TruthfulQA | Winogrande | GSM8K | | --- | --- | --- | --- | --- | --- | --- | --- | | Sakura-SOLRCA-Math-Instruct-DPO-v2 | 74.17 | 71.25 | 88.52 | 66.13 | 72.16 | 83.03 | 63.91 | | Sakura-SOLRCA-Math-Instruct-DPO-v1 | 74.13 | 71.25 | 88.48 | 66.21 | 72.12 | 82.87 | 63.84 | | Sakura-SOLRCA-Instruct-DPO | 74.05 | 71.16 | 88.49 | 66.17 | 72.10 | 82.95 | 63.46 | | Sakura-SOLAR-Instruct-DPO-v2 | 74.14 | 70.90 | 88.41 | 66.48 | 71.86 | 83.43 | 63.76 | | [kyujinpy/Sakura-SOLAR-Instruct](https://huggingface.co/kyujinpy/Sakura-SOLAR-Instruct) | 74.40 | 70.99 | 88.42 | 66.33 | 71.79 | 83.66 | 65.20 | # Implementation Code ```python ### KO-Platypus from transformers import AutoModelForCausalLM, AutoTokenizer import torch repo = "kyujinpy/Sakura-SOLRCA-Math-Instruct-DPO-v1" OpenOrca = AutoModelForCausalLM.from_pretrained( repo, return_dict=True, torch_dtype=torch.float16, device_map='auto' ) OpenOrca_tokenizer = AutoTokenizer.from_pretrained(repo) ``` ---