---
tags:
    - text-generation
license: cc-by-nc-4.0
language:
    - ko
base_model: upstage/SOLAR-10.7B-Instruct-v1.0
pipeline_tag: text-generation
---

# **DataVortexS-10.7B-dpo-v1.0**

<img src="./DataVortex.png" alt="DataVortex" style="height: 8em;">

## Our Team

| Research & Engineering | Product Management |
| :--------------------: | :----------------: |
|     Kwangseok Yang     |   Seunghyun Choi   |
|     Jeongwon Choi      |    Hyoseok Choi    |

## **Model Details**

### **Base Model**

[upstage/SOLAR-10.7B-Instruct-v1.0](https://huggingface.co/upstage/SOLAR-10.7B-Instruct-v1.0)

### **Trained On**

-   **OS**: Ubuntu 22.04
-   **GPU**: H100 80GB 4ea
-   **transformers**: v4.36.2

### **Instruction format**

It follows **Alpaca (Chat)** format.

E.g.

```python
text = """\
### System:
당신은 사람들이 정보를 찾을 수 있도록 도와주는 인공지능 비서입니다.

### User:
대한민국의 수도는 어디야?

### Assistant:
대한민국의 수도는 서울입니다.

### User:
서울 인구는 총 몇 명이야?
"""
```

## **Model Benchmark**

### **[Ko LM Eval Harness](https://github.com/Beomi/ko-lm-evaluation-harness)**

| Task             |         0-shot |       5-shot |        10-shot |        50-shot |
| :--------------- | -------------: | -----------: | -------------: | -------------: |
| kobest_boolq     |       0.867265 |     0.930834 |       0.938736 |       0.938023 |
| kobest_copa      |       0.722438 |     0.792716 |       0.782842 |       0.805869 |
| kobest_hellaswag |       0.484781 |     0.480055 |       0.496734 |       0.501488 |
| kobest_sentineg  |       0.759887 |     0.964735 |       0.964735 |       0.972291 |
| **Average**      | **0.70859275** | **0.792085** | **0.79576175** | **0.80441775** |

### **[Ko-LLM-Leaderboard](https://huggingface.co/spaces/upstage/open-ko-llm-leaderboard)**

| Average | Ko-ARC | Ko-HellaSwag | Ko-MMLU | Ko-TruthfulQA | Ko-CommonGen V2 |
| ------: | -----: | -----------: | ------: | ------------: | --------------: |
|   57.92 |  56.91 |        65.81 |   53.81 |         58.77 |           54.31 |

## **Implementation Code**

This model contains the chat_template instruction format.  
You can use the code below.

```python
from transformers import AutoModelForCausalLM, AutoTokenizer

device = "cuda" # the device to load the model onto

model = AutoModelForCausalLM.from_pretrained("Edentns/DataVortexS-10.7B-dpo-v1.0")
tokenizer = AutoTokenizer.from_pretrained("Edentns/DataVortexS-10.7B-dpo-v1.0")

messages = [
    {"role": "system", "content": "당신은 사람들이 정보를 찾을 수 있도록 도와주는 인공지능 비서입니다."},
    {"role": "user", "content": "대한민국의 수도는 어디야?"},
    {"role": "assistant", "content": "대한민국의 수도는 서울입니다."},
    {"role": "user", "content": "서울 인구는 총 몇 명이야?"}
]

encodeds = tokenizer.apply_chat_template(messages, return_tensors="pt")

model_inputs = encodeds.to(device)
model.to(device)

generated_ids = model.generate(model_inputs, max_new_tokens=1000, do_sample=True)
decoded = tokenizer.batch_decode(generated_ids)
print(decoded[0])
```

## **License**

This model is licensed under the [upstage/SOLAR-10.7B-Instruct-v1.0](https://huggingface.co/upstage/SOLAR-10.7B-Instruct-v1.0) license, with the [cc-by-nc-4.0](https://creativecommons.org/licenses/by-nc/4.0/) license granted. Under this license, others are allowed to copy, modify, and share the work, as long as it is not used for commercial purposes. They must provide appropriate credit and distribute any derivative works under the same license. For more details, please refer to the [cc-by-nc-4.0](https://creativecommons.org/licenses/by-nc/4.0/) license.

<div align="center">
    <a href="https://edentns.com/">
        <img src="./Logo.png" alt="Logo" style="height: 3em;">
    </a>
</div>