Upload README.md

README.md

@@ -1,3 +1,56 @@
 ---
+language:
+- ko
+datasets:
+- kyujinpy/OpenOrca-ko-v2
+library_name: transformers
+pipeline_tag: text-generation
 license: cc-by-nc-sa-4.0
 ---
+**(주)미디어그룹사람과숲과 (주)마커의 LLM 연구 컨소시엄에서 개발된 모델입니다**  
+**The license is `cc-by-nc-sa-4.0`.**  
+
+# **🐳Korean-OpenOrca-13B-v2🐳**  
+![img](./Korean-OpenOrca.png)  
+
+## Model Details
+
+**Model Developers** Kyujin Han (kyujinpy)
+
+**Model Architecture**  
+Korean-OpenOrca-13B is an auto-regressive language model based on the LLaMA2 transformer architecture.
+
+**Repo Link**  
+Github Korean-OpenOrca: [🐳Korean-OpenOrca🐳](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**  
+I use [OpenOrca-ko-v2](https://huggingface.co/datasets/kyujinpy/OpenOrca-ko-v2).  
+Using DeepL, translate about [OpenOrca](https://huggingface.co/datasets/Open-Orca/OpenOrca).
+
+I use A100 GPU 40GB and COLAB, when trianing.
+
+# Model comparisons
+| Model | Average |Ko-ARC | Ko-HellaSwag | Ko-MMLU | Ko-TruthfulQA | Ko-CommonGen V2 |
+| --- | --- | --- | --- | --- | --- | --- |
+| [Korean-OpenOrca-13B🐳] | 48.79 | 43.09 | 54.13 | 40.24 | 45.22 | 61.28 |  
+| Korean-OpenOrca-13B-v2🐳 | 48.17 | 43.17 | 54.51 | 42.90 | 41.82 | 58.44 | 
+
+# Implementation Code
+```python
+### KO-Platypus
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+repo = "kyujinpy/Korean-OpenOrca-13B-v2"
+OpenOrca = AutoModelForCausalLM.from_pretrained(
+        repo,
+        return_dict=True,
+        torch_dtype=torch.float16,
+        device_map='auto'
+)
+OpenOrca_tokenizer = AutoTokenizer.from_pretrained(repo)
+```
+
+---