File size: 1,379 Bytes
32b7ef6
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
---
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
---

**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 μ˜ν•œ λ²ˆμ—­ 데이터 일뢀](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:
μ‹œμŠ€ν…œ λ©”μ‹œμ§€ μž…λ‹ˆλ‹€. 
### User:
μœ μ €  μž…λ‹ˆλ‹€.
### Assistant
μ–΄μ‹œμŠ€ν„΄νŠΈ μž…λ‹ˆλ‹€.
```