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---
language:
- ko
datasets:
- kyujinpy/KOR-OpenOrca-Platypus-v3
library_name: transformers
pipeline_tag: text-generation
license: cc-by-nc-sa-4.0
---
# **Ko-PlatYi-6B-O**
<img src='./Ko-PlatYi.png' width=256>
## Model Details
**Model Developers** Kyujin Han (kyujinpy)
**Input** Models input text only.
**Output** Models generate text only.
**Model Architecture**
Ko-PlatYi-6B-O is an auto-regressive language model based on the Yi-34B transformer architecture.
**Blog Link**
Blog: [Coming soon...]
Github: [Coming soon...]
**Base Model**
[beomi/Yi-Ko-6B](https://huggingface.co./beomi/Yi-Ko-6B)
**Training Dataset**
[kyujinpy/KOR-OpenOrca-Platypus-v3](https://huggingface.co./datasets/kyujinpy/KOR-OpenOrca-Platypus-v3).
# **Model Benchmark**
## Open leaderboard
- Follow up as [link](https://huggingface.co./spaces/upstage/open-ko-llm-leaderboard).
| Model | Average | ARC | HellaSwag | MMLU | TruthfulQA | CommonGen-V2 |
| --- | --- | --- | --- | --- | --- | --- |
| **Ko-PlatYi-6B-O** | NaN | NaN | NaN | NaN | NaN | NaN |
| Ko-PlatYi-6B | NaN | NaN | NaN | NaN | NaN | NaN |
| Yi-Ko-6B | 48.79 | 41.04 | 53.39 | 46.28 | 41.64 | 61.63 |
# Implementation Code
```python
### KO-Platypus
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch
repo = "kyujinpy/Ko-PlatYi-6B-O"
OpenOrca = AutoModelForCausalLM.from_pretrained(
repo,
return_dict=True,
torch_dtype=torch.float16,
device_map='auto'
)
OpenOrca_tokenizer = AutoTokenizer.from_pretrained(repo)
```
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