---
license: apache-2.0
datasets:
- squarelike/sharegpt_deepl_ko_translation
language:
- en
- ko
pipeline_tag: translation
---

# Gugugo-koen-7B-V1.1
Detail repo: [https://github.com/jwj7140/Gugugo](https://github.com/jwj7140/Gugugo)
![Gugugo](./logo.png)

**Base Model**: [Llama-2-ko-7b](https://huggingface.co./beomi/llama-2-ko-7b)

**Training Dataset**: [sharegpt_deepl_ko_translation](https://huggingface.co./datasets/squarelike/sharegpt_deepl_ko_translation).

I trained with 1x A6000 GPUs for 90 hours.

## **Prompt Template**
**KO->EN**
```
### 한국어: {sentence}</끝>
### 영어:
```
**EN->KO**
```
### 영어: {sentence}</끝>
### 한국어:
```

## **Implementation Code**
```python
from vllm import LLM, SamplingParams

def make_prompt(data):
    prompts = []
    for line in data:
        prompts.append(f"### 영어: {line}</끝>\n### 한국어:")
    return prompts

texts = [
  "Hello world!",
  "Nice to meet you!"
]

prompts = make_prompt(texts)

sampling_params = SamplingParams(temperature=0.01, stop=["</끝>"], max_tokens=700)

llm = LLM(model="squarelike/Gugugo-koen-7B-V1.1-AWQ", quantization="awq", dtype="half")

outputs = llm.generate(prompts, sampling_params)

# Print the outputs.
for output in outputs:
    print(output.outputs[0].text)
```