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Update @ 2024.01.29 Released Yi-Ko(KoEN)-DUS-9B model 🎉


Yi-Ko-DUS model serves as DUS-applied and advanced iterations of beomi/Yi-Ko-6B model, benefiting from an expanded vocabulary and the inclusion of Korean/English corpus in its further pretraining.

Yi-Ko-DUS model operates with 9B billion parameters.

This repository focuses on the 9B pretrained version, which is tailored to fit the Hugging Face Transformers format, trained after DUS method applied.

Model Details

Model Developers Junbum Lee (Beomi), Taekyoon Choi (Taekyoon)

Variations Yi-Ko-DUS has 9B model only.

Input Models input text only.

Output Models generate text only.

Model Architecture

Yi-Ko-DUS series models are an auto-regressive language model that uses an optimized transformer architecture based on Llama-2*.

*Yi model architecture is based on Llama2, so it can be loaded via LlamaForCausalLM class on HF.

Model Name Training Data Params Context Length GQA Trained Tokens LR Batch Size(per step)
Yi-Ko-DUS-9B A mix of Korean + English online data 9B 4k O >120B 5e-5 2M tokens

Vocab Expansion

Model Name Vocabulary Size Description
Original Yi-Series 64000 Sentencepiece BPE
Expanded Yi-Ko(DUS) Series 78464 Sentencepiece BPE. Added Korean vocab and merges

Tokenizing "안녕하세요, 오늘은 날씨가 좋네요.ㅎㅎ"

Model # of tokens Tokens
Original Yi-Series 47 ['<0xEC>', '<0x95>', '<0x88>', '<0xEB>', '<0x85>', '<0x95>', '하', '<0xEC>', '<0x84>', '<0xB8>', '<0xEC>', '<0x9A>', '<0x94>', ',', '▁', '<0xEC>', '<0x98>', '<0xA4>', '<0xEB>', '<0x8A>', '<0x98>', '은', '▁', '<0xEB>', '<0x82>', '<0xA0>', '<0xEC>', '<0x94>', '<0xA8>', '가', '▁', '<0xEC>', '<0xA2>', '<0x8B>', '<0xEB>', '<0x84>', '<0xA4>', '<0xEC>', '<0x9A>', '<0x94>', '.', '<0xE3>', '<0x85>', '<0x8E>', '<0xE3>', '<0x85>', '<0x8E>']
Expanded Yi-Ko(DUS) Series 10 ['▁안녕', '하세요', ',', '▁오늘은', '▁날', '씨가', '▁좋네요', '.', 'ㅎ', 'ㅎ']
*Equal Korean vocab with Llama-2-Ko Series

Tokenizing "Llama 2: Open Foundation and Fine-Tuned Chat Models"

Model # of tokens Tokens
Original Yi-Series 21 ['The', '▁Y', 'i', '▁series', '▁models', '▁are', '▁large', '▁language', '▁models', '▁trained', '▁from', '▁scratch', '▁by', '▁developers', '▁at', '▁', '0', '1', '.', 'AI', '.']
Expanded Yi-Ko(DUS) Series 21 ['▁The', '▁Y', 'i', '▁series', '▁models', '▁are', '▁large', '▁language', '▁models', '▁trained', '▁from', '▁scratch', '▁by', '▁developers', '▁at', '▁', '0', '1', '.', 'AI', '.']
*Equal Korean vocab with Llama-2-Ko Series *Since Expanded Yi-Ko Series prepends _ at the beginning of the text(to ensure same tokenization for Korean sentences), it shows negilible difference for the first token on English tokenization.

Model Benchmark

5-shot Korean Dataset Evaluation

KMMLU: 43.3514 (exact_match, kmmlu_direct)

KorQuAD: 80.8798 (exact_match)

NSMC: 88.352 (acc)

KOBEST COPA: 84.4831 (macro_f1)

KOBEST HellaSwag: 52.6099 (macro_f1)

Apeach: Korean HateSpeech: 63.4723 (macro_f1)


Yi Series Models Community License Agreement

For commercial purpose, Follow Yi Series Models Community License Agreement to acquire Yi Series commercial license, and mailto: jun@beomi.net to acquire Yi-Ko sereis commercial license.


Please use this bibtex below:

@misc {lee_junbum_2024,
    author       = { {Lee Junbum, Choi Taekyoon} },
    title        = { Yi-Ko-DUS-9B },
    year         = 2024,
    url          = { https://huggingface.co/beomi/Yi-Ko-DUS-9B },
    doi          = { 10.57967/hf/1707 },
    publisher    = { Hugging Face }


The training is supported by TPU Research Cloud program.

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