Introduction
The model was trained to translate a single sentence from English to Korean with a 1.18M dataset in the general domain. Dataset: nayohan/aihub-en-ko-translation-1.2m
Loading the Model
Use the following Python code to load the model:
from transformers import AutoModelForCausalLM, AutoTokenizer
model_name = "nayohan/llama3-8b-it-translation-general-en-ko-1sent"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(
model_name,
device_map="auto",
torch_dtype=torch.bfloat16
)
Generating Text
To generate text, use the following Python code: Currently, this model only support English to Korean, not other languages or reverse and styles.
style="written"
SYSTEM_PROMPT=f"Acts as a translator. Translate en sentences into ko sentences in {style} style."
s = "The aerospace industry is a flower in the field of technology and science."
conversation = [{'role': 'system', 'content': SYSTEM_PROMPT},
{'role': 'user', 'content': s}]
inputs = tokenizer.apply_chat_template(
conversation,
tokenize=True,
add_generation_prompt=True,
return_tensors='pt'
).to("cuda")
outputs = model.generate(inputs, max_new_tokens=256)
print(tokenizer.decode(outputs[0][len(inputs[0]):]))
# Result
# INPUT: <|begin_of_text|><|start_header_id|>system<|end_header_id|>\n\nActs as a translator. Translate en sentences into ko sentences in colloquial style.<|eot_id|><|start_header_id|>user<|end_header_id|>\n\nThe aerospace industry is a flower in the field of technology and science.<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n
# OUTPUT: 항공 우주 산업은 기술과 과학의 꽃입니다.<|eot_id|>
# INPUT: <|begin_of_text|><|start_header_id|>system<|end_header_id|>\n\nActs as a translator. Translate en sentences into ko sentences in colloquial style.<|eot_id|><|start_header_id|>user<|end_header_id|>\n\n
Technical and basic sciences are very important in terms of research. It has a significant impact on the industrial development of a country. Government policies control the research budget.<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n
# OUTPUT: 기술과 기초과학은 연구 측면에서 매우 중요합니다. 한 국가의 산업 발전에 큰 영향을 미칩니다. 정부 정책은 연구 예산을 통제합니다.<|eot_id|>
Citation
@article{llama3modelcard,
title={Llama 3 Model Card},
author={AI@Meta},
year={2024},
url={https://github.com/meta-llama/llama3/blob/main/MODEL_CARD.md}
}
Our trainig code can be found here: [TBD]
- Downloads last month
- 155
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.