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README.md
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---
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license: cc-by-nc-4.0
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---
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---
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language:
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- ko
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datasets:
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- kyujinpy/OpenOrca-KO
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library_name: transformers
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pipeline_tag: text-generation
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license: cc-by-nc-4.0
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---
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# **Korean-OpenOrca-13B**
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## Model Details
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**Model Developers** Kyujin Han (kyujinpy)
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**Input** Models input text only.
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**Output** Models generate text only.
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**Model Architecture**
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Korean-OpenOrca-13B is an auto-regressive language model based on the LLaMA2 transformer architecture.
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**Repo Link**
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Github KoT-platypus: (Coming soon...)
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**Base Model** [hyunseoki/ko-en-llama2-13b](https://huggingface.co/hyunseoki/ko-en-llama2-13b)
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**Training Dataset**
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I use [OpenOrca-KO](https://huggingface.co/datasets/kyujinpy/OpenOrca-KO).
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Using DeepL, translate about [OpenOrca](https://huggingface.co/datasets/Open-Orca/OpenOrca).
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I use A100 GPU 40GB and COLAB, when trianing.
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# **Model Benchmark**
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## KO-LLM leaderboard
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- Follow up as [Open KO-LLM LeaderBoard](https://huggingface.co/spaces/upstage/open-ko-llm-leaderboard).
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| Model | Average |Ko-ARC | Ko-HellaSwag | Ko-MMLU | Ko-TruthfulQA | Ko-CommonGen V2 |
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| --- | --- | --- | --- | --- | --- | --- |
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| Korean-OpenOrca-13B(ours) | NaN | NaN | NaN | NaN | NaN | NaN |
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| [KoT-Platypus2-13B](https://huggingface.co/kyujinpy/KoT-platypus2-13B) | 49.55 | 43.69 | 53.05 | 42.29 | 43.34 | 65.38 |
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| [KO-Platypus2-13B](https://huggingface.co/kyujinpy/KO-Platypus2-13B) | 47.90 | 44.20 | 54.31 | 42.47 | 44.41 | 54.11 |
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| [hyunseoki/ko-en-llama2-13b](https://huggingface.co/hyunseoki/ko-en-llama2-13b) | 46.68 | 42.15 | 54.23 | 38.90 | 40.74 | 57.39 |
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| [MarkrAI/kyujin-CoTy-platypus-ko-12.8b](https://huggingface.co/MarkrAI/kyujin-CoTy-platypus-ko-12.8b) | 46.44 | 34.98 | 49.11 | 25.68 | 37.59 | 84.86 |
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> Compare with Top 4 SOTA models. (update: 10/09)
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# Implementation Code
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```python
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### KO-Platypus
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from transformers import AutoModelForCausalLM, AutoTokenizer
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import torch
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repo = "kyujinpy/Korean-OpenOrca-13B"
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OpenOrca = AutoModelForCausalLM.from_pretrained(
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repo,
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return_dict=True,
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torch_dtype=torch.float16,
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device_map='auto'
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)
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OpenOrca_tokenizer = AutoTokenizer.from_pretrained(repo)
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```
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---
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