metadata

library_name: transformers
license: apache-2.0
base_model:
  - Saxo/Linkbricks-Horizon-AI-Korean-Advanced-27B
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

AI 와 빅데이터 분석 전문 기업인 Linkbricks의 데이터사이언티스트인 지윤성(Saxo) 이사가
gemma-2-27b-it 베이스모델을 사용해서 H100-80G 8개를 통해 약 20%정도의 파라미터를 한국어 CPT(Continued-Pretraining)->SFT->DPO 한
한글 언어 모델인 Saxo/Linkbricks-Horizon-AI-Korean-Advanced-27B을 추가적인 한글데이터들을 활용해서 다양한 테스크별 한국어-중국어-영어-일본어 교차 학습 데이터와 수학 및
논리판단 데이터를 통하여 한중일영 언어 교차 증강 처리와 복잡한 논리 문제 역시 대응 가능하도록 훈련한 모델이다.
-영어처리 강화 버전
-토크나이저는 단어 확장 없이 베이스 모델 그대로 사용
-고객 리뷰나 복잡한 한글 추론 및 소셜 포스팅 고차원 분석 및 코딩과 작문, 수학, 논리판단 등이 강화된 모델
-128k-Context Window

Dr. Yunsung Ji (Saxo), a data scientist at Linkbricks, a company specializing in AI and big data analytics, has developed a Korean language model
using the Saxo/Linkbricks-Horizon-AI-Korean-Advanced-27B, a Korean language model that uses the gemma-2-27b-it basemodel to train about 20% of the parameters through 8 H100-80Gs
using Korean CPT (Continued-Pretraining)->SFT->DPO. It is a model trained to handle cross-lingual augmentation and complex logic problems by utilizing additional Korean data, cross-training data of Korean, Chinese, English, and Japanese by various tasks, and math and logic judgment data.

Translated with DeepL.com (free version)
-Reinforced English Language processing
-Tokenizer uses the base model without word expansion
-Models enhanced with high-dimensional analysis of customer reviews and social posts, as well as coding, writing, math, decision making and complex inference
-128k-Context Window
-Deepspeed Stage=3, use rslora and BAdam Layer Mode