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extra_gated_heading: Access beomi/Yi-Ko-6B on Hugging Face
extra_gated_button_content: Submit
extra_gated_fields:
  I agree to share my name, email address and username: checkbox
  I confirm that I understand this project is for research purposes only, and confirm that I agree to follow the LICENSE of this model: checkbox
language:
  - en
  - ko
pipeline_tag: text-generation
inference: false
tags:
  - pytorch
  - Yi-Ko
  - 01-ai
  - Yi
library_name: transformers

Update @ 2023.12.01 Alpha Release of Yi-Ko(KoEN)-6B model 🎉

beomi/Yi-Ko-6B

Yi-Ko series models serve as advanced iterations of 01-ai/Yi models, benefiting from an expanded vocabulary and the inclusion of Korean/English corpus in its further pretraining. Just like its predecessor, Yi-Ko series models operate within the broad range of generative text models that stretch from 6 billion to 34 billion parameters. This repository focuses on the 6B pretrained version, which is tailored to fit the Hugging Face Transformers format. For access to the other models, feel free to consult the index provided below.

Model Details

Model Developers Junbum Lee (Beomi)

Variations Yi-Ko series will come in a range of parameter sizes — 6B and 34B variations.

Input Models input text only.

Output Models generate text only.

Model Architecture

Yi-Ko 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-6B A mix of Korean + English online data 6B 4k O >60B 5e-5 2048

Vocab Expansion

Model Name Vocabulary Size Description
Original Yi-Series 64000 Sentencepiece BPE
Expanded Yi-Ko 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 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 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

LM Eval Harness - Korean (polyglot branch)

TBD

LICENSE

TBD

Citation

TBD

Acknowledgement

The training is supported by TPU Research Cloud program.