--- language: - ko datasets: - kyujinpy/OpenOrca-KO - kyujinpy/kyujinpy/KOpen-platypus library_name: transformers pipeline_tag: text-generation license: cc-by-nc-4.0 --- # **🐳KoR-Orca-Platypus-13B🐳** ![img](./Korean-OpenOrca.png) ## Model Details **Model Developers** Kyujin Han (kyujinpy) **Input** Models input text only. **Output** Models generate text only. **Model Architecture** KoR-Orca-Platypus-13B is an auto-regressive language model based on the LLaMA2 transformer architecture. **Repo Link** Github Korean-OpenOrca: [🐳KoR-Orca-Platypus-13B🐳](https://github.com/Marker-Inc-Korea/Korean-OpenOrca) **Base Model** [hyunseoki/ko-en-llama2-13b](https://huggingface.co/hyunseoki/ko-en-llama2-13b) **Training Dataset** Version of combined dataset: [kyujinpy/KOR-OpenOrca-Platypus](https://huggingface.co/datasets/kyujinpy/KOR-OpenOrca-Platypus) I combined [OpenOrca-KO](https://huggingface.co/datasets/kyujinpy/OpenOrca-KO) and [kyujinpy/KOpen-platypus](https://huggingface.co/datasets/kyujinpy/KOpen-platypus). I use A100 GPU 40GB and COLAB, when trianing. # **Model Benchmark** ## KO-LLM leaderboard - Follow up as [Open KO-LLM LeaderBoard](https://huggingface.co/spaces/upstage/open-ko-llm-leaderboard). | Model | Average |Ko-ARC | Ko-HellaSwag | Ko-MMLU | Ko-TruthfulQA | Ko-CommonGen V2 | | --- | --- | --- | --- | --- | --- | --- | | KoR-Orca-Platypus-13B🐳(ours) | NaN | NaN | NaN | NaN | NaN | NaN | | [GenAI-llama2-ko-en-platypus](https://huggingface.co/42MARU/GenAI-llama2-ko-en-platypus) | 49.81 | 45.22 | 55.25 | 41.84 | 44.78 | 61.97 | | [KoT-Platypus2-13B](https://huggingface.co/kyujinpy/KoT-platypus2-13B) | 49.55 | 43.69 | 53.05 | 42.29 | 43.34 | 65.38 | | [KO-Platypus2-13B](https://huggingface.co/kyujinpy/KO-Platypus2-13B) | 47.90 | 44.20 | 54.31 | 42.47 | 44.41 | 54.11 | | [Korean-OpenOrca-13B🐳](https://huggingface.co/kyujinpy/Korean-OpenOrca-13B) | 47.85 | 43.09 | 54.13 | 40.24 | 45.22 | 56.57 | > Compare with Top 4 SOTA models. (update: 10/14) # Implementation Code ```python ### KO-Platypus from transformers import AutoModelForCausalLM, AutoTokenizer import torch repo = "kyujinpy/KoR-Orca-Platypus-13B" OpenOrca = AutoModelForCausalLM.from_pretrained( repo, return_dict=True, torch_dtype=torch.float16, device_map='auto' ) OpenOrca_tokenizer = AutoTokenizer.from_pretrained(repo) ``` ---