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Update!

  • [2024.06.18] ์‚ฌ์ „ํ•™์Šต๋Ÿ‰์„ 250GB๊นŒ์ง€ ๋Š˜๋ฆฐ Bllossom ELO๋ชจ๋ธ๋กœ ์—…๋ฐ์ดํŠธ ๋˜์—ˆ์Šต๋‹ˆ๋‹ค. ๋‹ค๋งŒ ๋‹จ์–ดํ™•์žฅ์€ ํ•˜์ง€ ์•Š์•˜์Šต๋‹ˆ๋‹ค. ๊ธฐ์กด ๋‹จ์–ดํ™•์žฅ๋œ long-context ๋ชจ๋ธ์„ ํ™œ์šฉํ•˜๊ณ  ์‹ถ์œผ์‹ ๋ถ„์€ ๊ฐœ์ธ์—ฐ๋ฝ์ฃผ์„ธ์š”!
  • [2024.06.18] Bllossom ELO ๋ชจ๋ธ์€ ์ž์ฒด ๊ฐœ๋ฐœํ•œ ELO์‚ฌ์ „ํ•™์Šต ๊ธฐ๋ฐ˜์œผ๋กœ ์ƒˆ๋กœ์šด ํ•™์Šต๋œ ๋ชจ๋ธ์ž…๋‹ˆ๋‹ค. LogicKor ๋ฒค์น˜๋งˆํฌ ๊ฒฐ๊ณผ ํ˜„์กดํ•˜๋Š” ํ•œ๊ตญ์–ด 10B์ดํ•˜ ๋ชจ๋ธ์ค‘ SOTA์ ์ˆ˜๋ฅผ ๋ฐ›์•˜์Šต๋‹ˆ๋‹ค.

LogicKor ์„ฑ๋Šฅํ‘œ :

Model Math Reasoning Writing Coding Understanding Grammar Single ALL Multi ALL Overall
gpt-3.5-turbo-0125 7.14 7.71 8.28 5.85 9.71 6.28 7.50 7.95 7.72
gemini-1.5-pro-preview-0215 8.00 7.85 8.14 7.71 8.42 7.28 7.90 6.26 7.08
llama-3-Korean-Bllossom-8B 5.43 8.29 9.0 4.43 7.57 6.86 6.93 6.93 6.93

Bllossom | Demo | Homepage | Github

  • ๋ณธ ๋ชจ๋ธ์€ CPU์—์„œ ๊ตฌ๋™๊ฐ€๋Šฅํ•˜๋ฉฐ ๋น ๋ฅธ ์†๋„๋ฅผ ์œ„ํ•ด์„œ๋Š” 8GB GPU์—์„œ ๊ตฌ๋™ ๊ฐ€๋Šฅํ•œ ์–‘์žํ™” ๋ชจ๋ธ์ž…๋‹ˆ๋‹ค! Colab ์˜ˆ์ œ |
์ €ํฌ BllossomํŒ€ ์—์„œ ํ•œ๊ตญ์–ด-์˜์–ด ์ด์ค‘ ์–ธ์–ด๋ชจ๋ธ์ธ Bllossom์„ ๊ณต๊ฐœํ–ˆ์Šต๋‹ˆ๋‹ค!
์„œ์šธ๊ณผ๊ธฐ๋Œ€ ์Šˆํผ์ปดํ“จํŒ… ์„ผํ„ฐ์˜ ์ง€์›์œผ๋กœ 100GB๊ฐ€๋„˜๋Š” ํ•œ๊ตญ์–ด๋กœ ๋ชจ๋ธ์ „์ฒด๋ฅผ ํ’€ํŠœ๋‹ํ•œ ํ•œ๊ตญ์–ด ๊ฐ•ํ™” ์ด์ค‘์–ธ์–ด ๋ชจ๋ธ์ž…๋‹ˆ๋‹ค!
ํ•œ๊ตญ์–ด ์ž˜ํ•˜๋Š” ๋ชจ๋ธ ์ฐพ๊ณ  ์žˆ์ง€ ์•Š์œผ์…จ๋‚˜์š”?
 - ํ•œ๊ตญ์–ด ์ตœ์ดˆ! ๋ฌด๋ ค 3๋งŒ๊ฐœ๊ฐ€ ๋„˜๋Š” ํ•œ๊ตญ์–ด ์–ดํœ˜ํ™•์žฅ
 - Llama3๋Œ€๋น„ ๋Œ€๋žต 25% ๋” ๊ธด ๊ธธ์ด์˜ ํ•œ๊ตญ์–ด Context ์ฒ˜๋ฆฌ๊ฐ€๋Šฅ
 - ํ•œ๊ตญ์–ด-์˜์–ด Pararell Corpus๋ฅผ ํ™œ์šฉํ•œ ํ•œ๊ตญ์–ด-์˜์–ด ์ง€์‹์—ฐ๊ฒฐ (์‚ฌ์ „ํ•™์Šต)
 - ํ•œ๊ตญ์–ด ๋ฌธํ™”, ์–ธ์–ด๋ฅผ ๊ณ ๋ คํ•ด ์–ธ์–ดํ•™์ž๊ฐ€ ์ œ์ž‘ํ•œ ๋ฐ์ดํ„ฐ๋ฅผ ํ™œ์šฉํ•œ ๋ฏธ์„ธ์กฐ์ •
 - ๊ฐ•ํ™”ํ•™์Šต
์ด ๋ชจ๋“ ๊ฒŒ ํ•œ๊บผ๋ฒˆ์— ์ ์šฉ๋˜๊ณ  ์ƒ์—…์  ์ด์šฉ์ด ๊ฐ€๋Šฅํ•œ Bllossom์„ ์ด์šฉํ•ด ์—ฌ๋Ÿฌ๋ถ„ ๋งŒ์˜ ๋ชจ๋ธ์„ ๋งŒ๋“ค์–ด๋ณด์„ธ์šฅ!
๋ณธ ๋ชจ๋ธ์€ CPU์—์„œ ๊ตฌ๋™๊ฐ€๋Šฅํ•˜๋ฉฐ ๋น ๋ฅธ ์†๋„๋ฅผ ์œ„ํ•ด์„œ๋Š” 6GB GPU์—์„œ ๊ตฌ๋™ ๊ฐ€๋Šฅํ•œ ์–‘์žํ™” ๋ชจ๋ธ์ž…๋‹ˆ๋‹ค!

1. Bllossom-8B๋Š” ์„œ์šธ๊ณผ๊ธฐ๋Œ€, ํ…Œ๋””์ธ, ์—ฐ์„ธ๋Œ€ ์–ธ์–ด์ž์› ์—ฐ๊ตฌ์‹ค์˜ ์–ธ์–ดํ•™์ž์™€ ํ˜‘์—…ํ•ด ๋งŒ๋“  ์‹ค์šฉ์ฃผ์˜๊ธฐ๋ฐ˜ ์–ธ์–ด๋ชจ๋ธ์ž…๋‹ˆ๋‹ค! ์•ž์œผ๋กœ ์ง€์†์ ์ธ ์—…๋ฐ์ดํŠธ๋ฅผ ํ†ตํ•ด ๊ด€๋ฆฌํ•˜๊ฒ ์Šต๋‹ˆ๋‹ค ๋งŽ์ด ํ™œ์šฉํ•ด์ฃผ์„ธ์š” ๐Ÿ™‚
2. ์ดˆ ๊ฐ•๋ ฅํ•œ Advanced-Bllossom 8B, 70B๋ชจ๋ธ, ์‹œ๊ฐ-์–ธ์–ด๋ชจ๋ธ์„ ๋ณด์œ ํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค! (๊ถ๊ธˆํ•˜์‹ ๋ถ„์€ ๊ฐœ๋ณ„ ์—ฐ๋ฝ์ฃผ์„ธ์š”!!)
3. Bllossom์€ NAACL2024, LREC-COLING2024 (๊ตฌ๋‘) ๋ฐœํ‘œ๋กœ ์ฑ„ํƒ๋˜์—ˆ์Šต๋‹ˆ๋‹ค.
4. ์ข‹์€ ์–ธ์–ด๋ชจ๋ธ ๊ณ„์† ์—…๋ฐ์ดํŠธ ํ•˜๊ฒ ์Šต๋‹ˆ๋‹ค!! ํ•œ๊ตญ์–ด ๊ฐ•ํ™”๋ฅผ์œ„ํ•ด ๊ณต๋™ ์—ฐ๊ตฌํ•˜์‹ค๋ถ„(ํŠนํžˆ๋…ผ๋ฌธ) ์–ธ์ œ๋“  ํ™˜์˜ํ•ฉ๋‹ˆ๋‹ค!! 
   ํŠนํžˆ ์†Œ๋Ÿ‰์˜ GPU๋ผ๋„ ๋Œ€์—ฌ ๊ฐ€๋Šฅํ•œํŒ€์€ ์–ธ์ œ๋“  ์—ฐ๋ฝ์ฃผ์„ธ์š”! ๋งŒ๋“ค๊ณ  ์‹ถ์€๊ฑฐ ๋„์™€๋“œ๋ ค์š”.

The Bllossom language model is a Korean-English bilingual language model based on the open-source LLama3. It enhances the connection of knowledge between Korean and English. It has the following features:

  • Knowledge Linking: Linking Korean and English knowledge through additional training
  • Vocabulary Expansion: Expansion of Korean vocabulary to enhance Korean expressiveness.
  • Instruction Tuning: Tuning using custom-made instruction following data specialized for Korean language and Korean culture
  • Human Feedback: DPO has been applied
  • Vision-Language Alignment: Aligning the vision transformer with this language model

This model developed by MLPLab at Seoultech, Teddysum and Yonsei Univ. This model was converted to GGUF format from MLP-KTLim/llama-3-Korean-Bllossom-8B using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model.

Demo Video

Bllossom-V Demo

Bllossom Demo(Kakao)ใ…คใ…คใ…คใ…คใ…คใ…คใ…คใ…ค

NEWS

  • [2024.05.08] Vocab Expansion Model Update
  • [2024.04.25] We released Bllossom v2.0, based on llama-3
  • [2023/12] We released Bllossom-Vision v1.0, based on Bllossom
  • [2023/08] We released Bllossom v1.0, based on llama-2.
  • [2023/07] We released Bllossom v0.7, based on polyglot-ko.

Example code

!CMAKE_ARGS="-DLLAMA_CUDA=on" pip install llama-cpp-python
!huggingface-cli download MLP-KTLim/llama-3-Korean-Bllossom-8B-gguf-Q4_K_M --local-dir='YOUR-LOCAL-FOLDER-PATH'

from llama_cpp import Llama
from transformers import AutoTokenizer

model_id = 'MLP-KTLim/llama-3-Korean-Bllossom-8B-gguf-Q4_K_M'
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = Llama(
    model_path='YOUR-LOCAL-FOLDER-PATH/llama-3-Korean-Bllossom-8B-Q4_K_M.gguf',
    n_ctx=512,
    n_gpu_layers=-1        # Number of model layers to offload to GPU
)

PROMPT = \
'''๋‹น์‹ ์€ ์œ ์šฉํ•œ AI ์–ด์‹œ์Šคํ„ดํŠธ์ž…๋‹ˆ๋‹ค. ์‚ฌ์šฉ์ž์˜ ์งˆ์˜์— ๋Œ€ํ•ด ์นœ์ ˆํ•˜๊ณ  ์ •ํ™•ํ•˜๊ฒŒ ๋‹ต๋ณ€ํ•ด์•ผ ํ•ฉ๋‹ˆ๋‹ค.
You are a helpful AI assistant, you'll need to answer users' queries in a friendly and accurate manner.'''

instruction = 'Your Instruction'

messages = [
    {"role": "system", "content": f"{PROMPT}"},
    {"role": "user", "content": f"{instruction}"}
    ]

prompt = tokenizer.apply_chat_template(
    messages, 
    tokenize = False,
    add_generation_prompt=True
)

generation_kwargs = {
    "max_tokens":512,
    "stop":["<|eot_id|>"],
    "top_p":0.9,
    "temperature":0.6,
    "echo":True, # Echo the prompt in the output
}

resonse_msg = model(prompt, **generation_kwargs)
print(resonse_msg['choices'][0]['text'][len(prompt):])

Citation

Language Model

@misc{bllossom,
  author = {ChangSu Choi, Yongbin Jeong, Seoyoon Park, InHo Won, HyeonSeok Lim, SangMin Kim, Yejee Kang, Chanhyuk Yoon, Jaewan Park, Yiseul Lee, HyeJin Lee, Younggyun Hahm, Hansaem Kim, KyungTae Lim},
  title = {Optimizing Language Augmentation for Multilingual Large Language Models: A Case Study on Korean},
  year = {2024},
  journal = {LREC-COLING 2024},
  paperLink = {\url{https://arxiv.org/pdf/2403.10882}},
 },
}

Vision-Language Model

@misc{bllossom-V,
  author = {Dongjae Shin, Hyunseok Lim, Inho Won, Changsu Choi, Minjun Kim, Seungwoo Song, Hangyeol Yoo, Sangmin Kim, Kyungtae Lim},
  title = {X-LLaVA: Optimizing Bilingual Large Vision-Language Alignment},
  year = {2024},
  publisher = {GitHub},
  journal = {NAACL 2024 findings},
  paperLink = {\url{https://arxiv.org/pdf/2403.11399}},
 },
}

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