Create README.md

README.md

@@ -0,0 +1,62 @@
+---
+library_name: transformers
+license: apache-2.0
+base_model: mistralai/Mistral-Small-Instruct-2409
+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) 박사가 <br>
+Mistral-Small-Instruct-2409 베이스모델을 사용해서 H100-80G 8개를 통해 약 40%정도의 파라미터를 한국어 CPT(Continued-Pretraining)->SFT->DPO 한 한글 언어 모델<br>
+9천만건의 한글 뉴스 코퍼스를 기준으로 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.<br> 
+-토크나이저는 단어 확장 없이 베이스 모델 그대로 사용<br>
+-고객 리뷰나 소셜 포스팅 고차원 분석 및 코딩과 작문, 수학, 논리판단 등이 강화된 모델<br>
+-32k 시퀀스 길이<br> 
+-펑션콜 지원<br>
+-Deepspeed Stage=3, rslora 및 BAdam Layer Mode 사용 <br>
+<br><br>
+
+Finetuned by Mr. Yunsung Ji (Saxo), a data scientist at Linkbricks, a company specializing in AI and big data analytics <br>
+about 40% of total parameters Korean CPT(Continued-Pretraining)->SFT->DPO training model based on Mistral-Small-Instruct-2409 through 8 H100-80Gs as a Korean language model <br>
+It is a model that has been trained to handle Korean-Chinese-English-Japanese cross-training data and 90M korean news corpus and logic judgment data for various tasks to enable cross-fertilization processing and complex Korean logic & math problems. <br>
+-Tokenizer uses the base model without word expansion<br>
+-Models enhanced with high-dimensional analysis of customer reviews and social posts, as well as coding, writing, math and decision making<br>
+-32k sequence length<br> 
+-Function 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>