Bllossom
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llama-3.1-Korean-Bllossom-Vision-8B

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 ---
+language:
+- en
+- ko
+license: llama3.1
 library_name: transformers
+base_model:
+- meta-llama/Meta-Llama-3.1-8B
 ---
+<a href="https://github.com/MLP-Lab/Bllossom">
+  <img src="https://github.com/teddysum/bllossom/blob/main//bllossom_icon.png?raw=true" width="30%" height="30%">
+</a>
+# Update!
+* [2024.09.04] Bllossom의 시각-언어모델 preview 모델이 최초 업데이트 되었습니다.
+# Bllossom | [Demo]() | [Homepage](https://www.bllossom.ai/) | [Github](https://github.com/MLP-Lab/Bllossom) |
+<!-- [GPU용 Colab 코드예제](https://colab.research.google.com/drive/1fBOzUVZ6NRKk_ugeoTbAOokWKqSN47IG?usp=sharing) | -->
+<!-- [CPU용 Colab 양자화모델 코드예제](https://colab.research.google.com/drive/129ZNVg5R2NPghUEFHKF0BRdxsZxinQcJ?usp=drive_link) -->
+```bash
+저희 Bllossom 팀에서 llama3.1 기반의 한국어-영어 이중 언어모델 Bllossom-405B를 공개합니다.
+이번 Bllossom3.1-405B는 preview 버전으로 다음과 같은 특징을 보입니다.
+ - Llama3.1-405B-Inst 대비 5~10% 한국어 성능이 향상 되었습니다 (single turn 기준).
+ - Llama3.1의 영어 성능을 전혀 손상시키지 않은 완전한 Bilingual 모델입니다.
+ - 기존 모델 대비 자연스럽고 친절한 한국어 문장을 생성합니다.
+ - 인간평가, GPT평가(MT-Bench, LogicKor 9점 등) 결과 GPT4와 유사하거나 약간 낮은 성능을 보여줍니다.
+해당 모델은 다음과 같은 협업을 토대로 구축 되었습니다!
+ - 서울과기대 MLP연구실의 경량화 사전 학습기법이 적용되었습니다.
+ - 테디썸의 정교한 Instruction Tuning과 RAG 기술이 적용되었습니다.
+ - HP의 computing 지원이 있었습니다.
+ - Common Crawl 재단의 Oscar팀에서 적극적인 데이터 지원이 있었습니다
+언제나 그랬듯 해당 모델은 상업적 이용이 가능합니다. A100 6대만 준비되면 Bllossom을 이용해 여러분만의 모델을 만들어보세요 GPT4가 더이상 필요 없습니다.
+GPU자원이 부족하면 A100 3개 혹은 A6000 4개로 양자화 모델을 이용해 보세요. [양자화모델](https://huggingface.co/MLP-KTLim/llama-3.1-Korean-Bllossom-405B-gguf-Q4_K_M)
+1. Bllossom-8B는 서울과기대, 테디썸, 연세대 언어자원 연구실의 언어학자와 협업해 만든 실용주의기반 무료 언어모델로 2023년부터 지속적인 업데이트를 통해 관리해 오고있습니다. 많이 활용해주세요 🙂
+2. 초 강력한 Advanced-Bllossom 모델, 시각-언어 모델을 보유하고 있습니다! (궁금하신분은 개별 연락주세요!!)
+3. Bllossom은 NAACL2024, LREC-COLING2024 (구두) 발표되었습니다.
+4. 좋은 언어모델 계속 업데이트 하겠습니다!! 한국어 강화를위해 공동 연구하실분(특히논문) 언제든 환영합니다!!
+   그리고 소량의 GPU라도 대여 가능한팀은 언제든 연락주세요! 만들고 싶은거 도와드려요.
+```
+```bash
+The Bllossom language model is a Korean-English bilingual language model based on the open-source LLama3.1. It enhances the connection of knowledge between Korean and English. It has the following features:
+ - Korean performance improved by 5-10% compared to Llama 3.1-405B-Inst (on Single Turn Eval).
+ - A complete bilingual model that does not compromise the English performance of Llama 3.1.
+ - Generates more natural and friendly Korean sentences compared to existing models.
+ - Human evaluations and GPT evaluations (MT-Bench, LogicKor scoring 9, etc.) show performance similar to or slightly lower than GPT-4.
+```
+**This model developed by [MLPLab at Seoultech](http://mlp.seoultech.ac.kr), [Teddysum](http://teddysum.ai/) and [Yonsei Univ](https://sites.google.com/view/hansaemkim/hansaem-kim)**
+## Example code
+### Colab Tutorial
+ - [Inference-Code-Link](https://colab.research.google.com/drive/1fBOzUVZ6NRKk_ugeoTbAOokWKqSN47IG?usp=sharing)
+### Install Dependencies
+```bash
+pip install torch transformers==4.40.0 accelerate
+```
+### Python code with Pipeline
+```python
+import transformers
+import torch
+model_id = "Bllossom/llama-3.1-Korean-Bllossom-405B"
+pipeline = transformers.pipeline(
+    "text-generation",
+    model=model_id,
+    model_kwargs={"torch_dtype": torch.bfloat16},
+    device_map="auto",
+)
+pipeline.model.eval()
+PROMPT = '''You are a helpful AI assistant. Please answer the user's questions kindly. 당신은 유능한 AI 어시스턴트 입니다. 사용자의 질문에 대해 친절하게 답변해주세요.'''
+instruction = "서울의 유명한 관광 코스를 만들어줄래?"
+messages = [
+    {"role": "system", "content": f"{PROMPT}"},
+    {"role": "user", "content": f"{instruction}"}
+    ]
+prompt = pipeline.tokenizer.apply_chat_template(
+        messages,
+        tokenize=False,
+        add_generation_prompt=True
+)
+terminators = [
+    pipeline.tokenizer.eos_token_id,
+    pipeline.tokenizer.convert_tokens_to_ids("<|eot_id|>")
+]
+outputs = pipeline(
+    prompt,
+    max_new_tokens=2048,
+    eos_token_id=terminators,
+    do_sample=True,
+    temperature=0.6,
+    top_p=0.9
+)
+print(outputs[0]["generated_text"][len(prompt):])
+```
+```
+# 물론이죠! 서울은 다양한 문화와 역사, 자연을 겸비한 도시로, 많은 관광 명소를 자랑합니다. 여기 서울의 유명한 관광 코스를 소개해 드릴게요.
+### 코스 1: 역사와 문화 탐방
+1. **경복궁**
+   - 서울의 대표적인 궁궐로, 조선 왕조의 역사와 문화를 체험할 수 있는 곳입니다.
+2. **북촌 한옥마을**
+   - 전통 한옥이 잘 보존된 마을로, 조선시대의 생활상을 느낄 수 있습니다.
+...
+```
+## Supported by
+ - Hewlett Packard (HP) Enterprise  <img src="https://upload.wikimedia.org/wikipedia/commons/thumb/4/46/Hewlett_Packard_Enterprise_logo.svg/2880px-Hewlett_Packard_Enterprise_logo.svg.png" width="20%" height="20%">
+ - Common Crawl <img src="https://cdn.prod.website-files.com/6479b8d98bf5dcb4a69c4f31/649b5869af56f6df617cfb1f_CC_Logo_Blue_Auto.svg" width="20%" height="20%">
+ - AICA
+## Citation
+**Language Model**
+```text
+@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**
+```text
+@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}},
+ },
+}
+```
+## Contact
+ - 임경태(KyungTae Lim), Professor at Seoultech. `[email protected]`
+ - 함영균(Younggyun Hahm), CEO of Teddysum. `[email protected]`
+ - 김한샘(Hansaem Kim), Professor at Yonsei. `[email protected]`
+## Contributor
+ - **신동재(Dongjae Shin)**, [email protected]
+ - **임현석(Hyeonseok Lim)**, gustjrantk@seoultech.ac.kr
+ - 원인호(Inho Won), [email protected]
+ - 김민준(Minjun Kim), mjkmain@seoultech.ac.kr
+ - 유한결(Hangyeol Yoo), [email protected]
+ - 송승우(Seungwoo Song), [email protected]
+ - 육정훈(Jeonghun Yuk), [email protected]
+ - 최창수(Chansu Choi), [email protected]
+ - 송서현(Seohyun Song), [email protected]