Create README.md

README.md

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+---
+language:
+- en
+pipeline_tag: text-generation
+datasets:
+- nlpai-lab/databricks-dolly-15k-ko
+- kyujinpy/KOR-OpenOrca-Platypus-v3
+- KETI-AIR/kor_boolq
+- heegyu/open-korean-instructions
+license: cc-by-sa-4.0
+---
+
+**Input** Models input text only.
+
+**Output** Models generate text only.
+
+**Base Model**  [upstage/SOLAR-10.7B-Instruct-v1.0](https://huggingface.co/upstage/SOLAR-10.7B-Instruct-v1.0)   
+
+**Training Dataset**  
+- [nlpai-lab/databricks-dolly-15k-ko](https://huggingface.co/datasets/nlpai-lab/databricks-dolly-15k-ko)
+- [kyujinpy/KOR-OpenOrca-Platypus-v3](https://huggingface.co/datasets/kyujinpy/KOR-OpenOrca-Platypus-v3)
+- [heegyu/open-korean-instructions](heegyu/open-korean-instructions)
+- [KETI-AIR/kor_boolq](https://huggingface.co/datasets/KETI-AIR/kor_boolq)
+- [AIhub 영한 번역 데이터 일부](https://aihub.or.kr/aihubdata/data/view.do?currMenu=115&topMenu=100&dataSetSn=71593)
+
+# Implementation Code
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+repo = "ifuseok/sft-solar-10.7b-v1.1"
+OpenOrca = AutoModelForCausalLM.from_pretrained(
+        repo,
+        return_dict=True,
+        torch_dtype=torch.float16,
+        device_map='auto'
+)
+OpenOrca_tokenizer = AutoTokenizer.from_pretrained(repo)
+```
+
+# Prompt Example
+```
+### System:
+시스템 메시지 입니다. 
+### User:
+유저  입니다.
+### Assistant
+어시스턴트 입니다.
+```