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---
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🐳**
## 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)
```
--- |