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---
language:
- ko
- en
pipeline_tag: text-generation
tags:
- orca
- llama-2
---


<p align="center" width="100%">
<img src="https://i.imgur.com/snFDU0P.png" alt="KoreanLM icon" style="width: 500px; display: block; margin: auto; border-radius: 10%;">
</p>



# quantumaikr/llama-2-70b-fb16-korean

## Model Description

`quantumaikr/llama-2-70b-fb16-korean` is a Llama2 70B model finetuned the Korean Dataset

## Usage

Start chatting with `quantumaikr/llama-2-70b-fb16-korean` using the following code snippet:

```python
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline

tokenizer = AutoTokenizer.from_pretrained("quantumaikr/llama-2-70b-fb16-korean")
model = AutoModelForCausalLM.from_pretrained("quantumaikr/llama-2-70b-fb16-korean", torch_dtype=torch.float16, device_map="auto")

system_prompt = "### System:\n๊ท€ํ•˜๋Š” ์ง€์‹œ๋ฅผ ๋งค์šฐ ์ž˜ ๋”ฐ๋ฅด๋Š” AI์ธ QuantumLM์ž…๋‹ˆ๋‹ค. ์ตœ๋Œ€ํ•œ ๋งŽ์ด ๋„์™€์ฃผ์„ธ์š”. ์•ˆ์ „์— ์œ ์˜ํ•˜๊ณ  ๋ถˆ๋ฒ•์ ์ธ ํ–‰๋™์€ ํ•˜์ง€ ๋งˆ์„ธ์š”.\n\n"

message = "์ธ๊ณต์ง€๋Šฅ์ด๋ž€ ๋ฌด์—‡์ธ๊ฐ€์š”?"
prompt = f"{system_prompt}### User: {message}\n\n### Assistant:\n"
inputs = tokenizer(prompt, return_tensors="pt").to("cuda")
output = model.generate(**inputs, do_sample=True, temperature=0.9, top_p=0.75, max_new_tokens=4096)

print(tokenizer.decode(output[0], skip_special_tokens=True))
```

QuantumLM should be used with this prompt format:
```
### System:
This is a system prompt, please behave and help the user.

### User:
Your prompt here

### Assistant
The output of QuantumLM
```



## Use and Limitations

### Intended Use

These models are intended for research only, in adherence with the [CC BY-NC-4.0](https://creativecommons.org/licenses/by-nc/4.0/) license.

### Limitations and bias

Although the aforementioned dataset helps to steer the base language models into "safer" distributions of text, not all biases and toxicity can be mitigated through fine-tuning. We ask that users be mindful of such potential issues that can arise in generated responses. Do not treat model outputs as substitutes for human judgment or as sources of truth. Please use it responsibly.



Contact us : hi@quantumai.kr
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_quantumaikr__llama-2-70b-fb16-korean)

| Metric                | Value                     |
|-----------------------|---------------------------|
| Avg.                  | 56.97   |
| ARC (25-shot)         | 67.15          |
| HellaSwag (10-shot)   | 86.78    |
| MMLU (5-shot)         | 69.29         |
| TruthfulQA (0-shot)   | 56.5   |
| Winogrande (5-shot)   | 82.64   |
| GSM8K (5-shot)        | 29.04        |
| DROP (3-shot)         | 7.42         |