--- language: - ko - en library_name: transformers license: cc-by-nc-sa-4.0 pipeline_tag: text-generation tags: - pytorch --- ## Model Description 한국어 LLM 평가 데이터셋인 kollm 을 활용하여 Supervised Fine-Tuning(a.k.a SFT) 학습한 모델입니다. 학습 데이터셋은 KoAlpaca-v1.1, kollm_kmmlu, korean-parallel-corpora, kobest_sentineg 와 같은 오픈 데이터셋으로 구성되어 있습니다. 데이터에 대한 상세한 설명은 Train Datasets 링크를 참고해주세요. ## About the Model - **Name:** TwinDoc/RedWhale-tv-10.8B-sft-g - **Finetuned from model:** [TwinDoc/RedWhale-tv-10.8B-v1.0](https://huggingface.co/TwinDoc/RedWhale-tv-10.8B-v1.0) - **Train Datasets:** [davidkim205/kollm-converations](https://huggingface.co/datasets/davidkim205/kollm-converations?row=33) - **Developed by:** 애자일소다 (AGILESODA) - **Model type:** llama - **Language(s) (NLP):** 한국어, 영어 - **License:** cc-by-nc-sa-4.0 - **train setting** - Lora r, alpha : 64, 16 - Dtype : bf16 - Epoch : 1 - Learning rate : 2e-4 - Global batch : 128 - Context length : 1024 - **inference setting** - BOS id : 1 - EOS id : 2 - Top-p : 0.95 - Temperature : 0.01 ## prompt template ``` A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. Human: {input} Assistant: {output} ``` ## License The content of this project, created by AGILESODA, is licensed under the [Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)](https://creativecommons.org/licenses/by-nc-sa/4.0/). ## Citation ``` @misc{vo2024redwhaleadaptedkoreanllm, title={RedWhale: An Adapted Korean LLM Through Efficient Continual Pretraining}, author={Anh-Dung Vo and Minseong Jung and Wonbeen Lee and Daewoo Choi}, year={2024}, eprint={2408.11294}, archivePrefix={arXiv}, primaryClass={cs.CL}, url={https://arxiv.org/abs/2408.11294}, } ``` **Built with:** AgileSoda TwinDoc Icon