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README.md

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+
+
+---
+library_name: transformers
+license: apache-2.0
+language:
+- en
+- ko
+base_model:
+- meta-llama/Meta-Llama-3-8B
+---
+
+<a href="https://github.com//KULLM">
+  <img src="./bllossom_icon.png" width="40%" height="40%">
+</a>
+
+
+# Bllossom | [Demo](https://c537bba37aaab5fc9e.gradio.live) | [Homepage](https://www.bllossom.ai/) |
+
+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 devel by [MLPLab at Seoultech](http://mlp.seoultech.ac.kr), [Teddysum](http://teddysum.ai/) and [Yonsei Univ](https://sites.google.com/view/hansaemkim/hansaem-kim)**
+
+## NEWS
+* [2024/04] 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
+### Install Dependencies
+```bash
+pip install torch transformers==4.40.0 accelerate
+```
+
+### Python code with Pipeline
+```python
+import transformers
+import torch
+
+model_id = "MLP-KTLim/Bllossom"
+
+pipeline = transformers.pipeline(
+    "text-generation",
+    model=model_id,
+    model_kwargs={"torch_dtype": torch.bfloat16},
+    device_map="auto",
+)
+
+pipeline.model.eval()
+
+PROMPT = '''당신은 유용한 AI 어시스턴트입니다. 사용자의 질의에 대해 친절하고 정확하게 답변해야 합니다.'''
+instruction = "서울과학기술대학교 MLP연구실에 대해 소개해줘"
+
+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):])
+
+# 서울과학기술대학교 MLP연구실은 멀티모달 자연어처리 연구를 하고 있습니다. 구성원은 임경태 교수와 김민준, 김상민, 최창수, 원인호, 유한결, 임현석, 송승우, 육정훈, 신동재 학생이 있습니다.
+```
+
+### Python code with AutoModel
+```python
+
+import os
+import torch
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+model_id = 'MLP-KTLim/Bllossom'
+
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(
+    model_id,
+    torch_dtype=torch.bfloat16,
+    device_map="auto",
+)
+
+model.eval()
+
+PROMPT = '''당신은 유용한 AI 어시스턴트입니다. 사용자의 질의에 대해 친절하고 정확하게 답변해야 합니다.'''
+instruction = "서울과학기술대학교 MLP연구실에 대해 소개해줘"
+
+messages = [
+    {"role": "system", "content": f"{PROMPT}"},
+    {"role": "user", "content": f"{instruction}"}
+    ]
+
+input_ids = tokenizer.apply_chat_template(
+    messages,
+    add_generation_prompt=True,
+    return_tensors="pt"
+).to(model.device)
+
+terminators = [
+    tokenizer.eos_token_id,
+    tokenizer.convert_tokens_to_ids("<|eot_id|>")
+]
+
+outputs = model.generate(
+    input_ids,
+    max_new_tokens=2048,
+    eos_token_id=terminators,
+    do_sample=True,
+    temperature=0.6,
+    top_p=0.9,
+    repetition_penalty = 1.1
+)
+
+print(tokenizer.decode(outputs[0][input_ids.shape[-1]:], skip_special_tokens=True))
+# 서울과학기술대학교 MLP연구실은 멀티모달 자연어처리 연구를 하고 있습니다. 구성원은 임경태 교수와 김민준, 김상민, 최창수, 원인호, 유한결, 임현석, 송승우, 육정훈, 신동재 학생이 있습니다.
+```
+
+
+
+## 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,
+  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. `ktlim@seoultech.ac.kr`
+ - 함영균(Younggyun Hahm), CEO of Teddysum. `hahmyg@teddysum.ai`