README.md

---
library_name: transformers
license: apache-2.0
base_model:
- meta-llama/Llama-3.2-3B-Instruct
datasets:
- Saxo/ko_cn_translation_tech_social_science_linkbricks_single_dataset
- Saxo/ko_jp_translation_tech_social_science_linkbricks_single_dataset
- >-
  Saxo/en_ko_translation_tech_science_linkbricks_single_dataset_with_prompt_text_huggingface
- >-
  Saxo/en_ko_translation_social_science_linkbricks_single_dataset_with_prompt_text_huggingface
- >-
  Saxo/ko_aspect_sentiment_sns_mall_sentiment_linkbricks_single_dataset_with_prompt_text_huggingface
- Saxo/ko_summarization_linkbricks_single_dataset_with_prompt_text_huggingface
- >-
  Saxo/OpenOrca_cleaned_kor_linkbricks_single_dataset_with_prompt_text_huggingface
- >-
  Saxo/ko_government_qa_total_linkbricks_single_dataset_with_prompt_text_huggingface_sampled
- Saxo/ko-news-corpus-1
- Saxo/ko-news-corpus-2
- Saxo/ko-news-corpus-3
- Saxo/ko-news-corpus-4
- Saxo/ko-news-corpus-5
- Saxo/ko-news-corpus-6
- Saxo/ko-news-corpus-7
- Saxo/ko-news-corpus-8
- Saxo/ko-news-corpus-9
- maywell/ko_Ultrafeedback_binarized
- youjunhyeok/ko-orca-pair-and-ultrafeedback-dpo
- lilacai/glaive-function-calling-v2-sharegpt
- kuotient/gsm8k-ko
language:
- ko
- en
- jp
- cn
pipeline_tag: text-generation
---

# Model Card for Model ID

<div align="center">
<img src="https://www.linkbricks.com/wp-content/uploads/2022/03/%E1%84%85%E1%85%B5%E1%86%BC%E1%84%8F%E1%85%B3%E1%84%87%E1%85%B3%E1%84%85%E1%85%B5%E1%86%A8%E1%84%89%E1%85%B3%E1%84%85%E1%85%A9%E1%84%80%E1%85%A9-2-1024x804.png" />
</div>


AI 와 빅데이터 분석 전문 기업인 Linkbricks의 데이터사이언티스트인 지윤성(Saxo) 이사가 <br>
meta-llama/Llama-3.2-3B-Instruct 베이스모델을 사용해서 H100-80G 8개를 통해 CPT(Continued Pre Trainig) 한 한글 언어 모델<br>
5천만건의 한글 뉴스 포함 다양한 한글 코퍼스를 기준으로 전체 파라미터중 약 35%를 재 튜닝한 한글 기본 모델로 SFT, DPO 를 통해 용도에 맞게 튜닝하면 됩니다.<br>
-토크나이저는 확장 없이 베이스 모델을 그대로 사용<br> 
-128k-Context Window<br>
-한글 Function Call 및 Tool Calling 지원 <br>
-Deepspeed Stage=3, rslora 및 BAdam Layer Mode 사용 <br>
<br><br>

Dr. Yunsung Ji (Saxo), a data scientist at Linkbricks, a company specializing in AI and big data analytics <br>
Korean language model CPT (Continued Pre Trainig) with 8 H100-80Gs using meta-llama/Llama-3.2-3B-Instruct base model<br>
A basic Korean language model with about 35% of the total parameters re-tuned based on various Korean corpus including 50 million Korean news, which need to be customized through SFT and DPO.
<br><br>
-Tokenizer uses the base model without word expansion<br>
-128k-Context Window<br>
-Support for Korean Functioncall and Tool Calling<br>
-Deepspeed Stage=3, use rslora and BAdam Layer Mode<br>
<br><br>

<a href="www.linkbricks.com">www.linkbricks.com</a>, <a href="www.linkbricks.vc">www.linkbricks.vc</a>