--- language: - en Dataset: - argilla/distilabel-math-preference-dpo pipeline_tag: text-generation license: cc-by-nc-sa-4.0 --- # **Sakura-SOLAR-Instruct-DPO-v1** ## Model Details **Model Developers** Kyujin Han (kyujinpy) **Method** Using [Mergekit](https://github.com/cg123/mergekit). I shared the information about my model. (training and code) Please see: [⭐Sakura-SOLAR(will update)](). # **Model Benchmark** ## Open leaderboard - Follow up as [link](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). | Model | Average | ARC | HellaSwag | MMLU | TruthfulQA | Winogrande | GSM8K | | --- | --- | --- | --- | --- | --- | --- | --- | | akura-SOLAR-Instruct-DPO-v2 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | | Sakura-SOLAR-Instruct-DPO-v1 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | | [kyujinpy/Sakura-SOLAR-Instruct](https://huggingface.co/kyujinpy/Sakura-SOLAR-Instruct) | NaN | NaN | NaN | NaN | NaN | NaN | NaN | # Implementation Code ```python ### KO-Platypus from transformers import AutoModelForCausalLM, AutoTokenizer import torch repo = "kyujinpy/Sakura-SOLAR-Instruct" OpenOrca = AutoModelForCausalLM.from_pretrained( repo, return_dict=True, torch_dtype=torch.float16, device_map='auto' ) OpenOrca_tokenizer = AutoTokenizer.from_pretrained(repo) ``` ---