safetensors llama arxiv:1910.09700 8-bit bitsandbytes region:us
---
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---
Quantization made by Richard Erkhov.

[Github](https://github.com/RichardErkhov)

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Llama-3.2-3B-KO-EN-Translation - bnb 8bits
- Model creator: https://huggingface.co/kwoncho/
- Original model: https://huggingface.co/kwoncho/Llama-3.2-3B-KO-EN-Translation/




Original model description:
---
library_name: transformers
tags: []
---

# Model Card for Model ID

한국어/영어 번역용으로 훈련한 모형입니다. llama3.2의 경우 한국어-영어 번역에 오류가 잦아 별도로 훈련시켰습니다.
성능향상을 위해 추가훈련을 진행했습니다.

아래 사항에 주의해 주세요:
- 이 모델은 문장단위 번역으로 훈련시켰습니다. 따라서 긴 텍스트의 경우 번역에 오류가 있을 수 있습니다. 또한 인풋 텍스트에 줄바꿈이 있을 경우 결과물을 추출하는데 복잡해질 수 있습니다.
- 이 모델의 주 용도는 금융/경영 관련으로 상정하고 훈련했습니다.
- 총 47만여개의 금융 관련 문장 페어를 사용하여 훈련하였습니다. 추가로 약 50여만개의 일반 문장을 사용하였습니다.
- 이하 모델카드는 시간이 나는대로 추가하겠습니다.
- 주의할 몇몇 점
  - 숫자 등을 마음대로 생성하는 경우가 있어, "퍼센트, 금액, 숫자는 본문의 숫자를 그대로 사용하세요."" 등의 프롬프트를 추가하는 등을 고려해 주시기 바랍니다.
  - 영한 번역은 성능이 상당히 부족합니다.
  
- 사용에 있어, 아래 코드를 참고해주세요:


  ```
  from transformers import AutoModelForCausalLM, AutoTokenizer
  import torch
  model_path = "kwoncho/Llama-3.2-3B-KO-EN-Translation"
  model = AutoModelForCausalLM.from_pretrained(
      model_path,
      torch_dtype=torch.bfloat16,
      device_map="cuda:0",
      )
  tokenizer = AutoTokenizer.from_pretrained(model_path)
  ```
- 한국어 -> 영어의 경우
  ```
  test_input = "삼성생명이 프랑스의 인프라 투자 전문 운용사의 2대 주주로 올랐다."
  prompt = f"""
    ### Instruction:
    주어진 텍스트를 영어로 번역하세요.
    ### Input:
    {test_input}
    ### Output:
    """
  ```
- 영어 -> 한국어의 경우
  ```
  test_input = """Retailers were “incentivising via discounts and different forms of promotions” for those at the lower end of the income spectrum while also “trying to grab higher-income individuals to make purchases during this wider window”, he said."""
  prompt = f"""
    ### Instruction:
    주어진 텍스트를 한국어로 번역하세요.
    ### Input:
    {test_input}
    ### Output:
    """
  ```

```
input_ids = tokenizer.encode(prompt, return_tensors="pt").to(model.device)
output = model.generate(
    input_ids,
    max_new_tokens=200,
    temperature=0.1,
    top_p=1,
    repetition_penalty=1.3,
    do_sample=True,
    eos_token_id=tokenizer.eos_token_id
    )
generated_text = tokenizer.decode(output[0], skip_special_tokens=True)
outputs        = generated_text.split("Output:")[1].strip().split('\n')[0].strip()
print(outputs) ### 한영 번역의 경우
"Samsung Life Insurance has become the second-largest shareholder of a French infrastructure investment management company."

print(outputs) ### 영한 번역의 경우
"그는 "소매상들은 소득 하위층을 대상으로 할부, 할인 등 다양한 형태의 인센티브를 제공하면서도 상위 계층의 고객들을 끌어모으려 하고 있다"고 말했다."
```

## Model Details

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- **Developed by:** Hyunkwon Cho (Kwon Cho)
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