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Model: unidocs/llama-3.1-8b-komedic-instruct Source: Original Platform
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README.md
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---
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license: mit
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language:
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- en
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- ko
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metrics:
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- accuracy
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base_model:
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- meta-llama/Llama-3.1-8B-Instruct
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library_name: transformers
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tags:
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- medical
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- healthcare
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---
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# LLaMA 3.1 8B Instruct - Healthcare Fine-tuned Model
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This is a model that fine-tuned the Llama-3.1-8B-Instruct model from Unidocs using Healthcare data.<br>
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유니닥스(주)에서 Llama-3.1-8B-Instruct 모델을 Healthcare 데이터로 미세조정한 모델임 <br>
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## Model Description
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sLLM model used in Unidoc's ezMyAIDoctor, released on October 16, 2024 as a result of the AIDC-HPC project <br>
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of the Artificial Intelligence Industry Convergence Business Group (AICA) <br>
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meta-llama/Llama-3.1-8B-Instruct wiki, kowiki, super-large AI healthcare question-answer data, <br>
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A model that has been pretrained (Full Finetuning) by referring to the super-large AI corpus with improved Korean performance, <br>
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and the medical and legal professional book corpus.
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유니닥스(주)의 ezMyAIDoctor에서 사용되는 sLLM 모델로 인공지능산업융합사업단(AICA)의 AIDC-HPC 사업의 결과로 2024년 10월 16일 공개함<br>
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meta-llama/Llama-3.1-8B-Instruct에 wiki, kowiki, AIHub(aihub.or.kr)의 (초거대AI 헬스케어 질의응답데이터,
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한국어 성능이 개선된 초거대 AI 말뭉치, 의료/법률 전문서적 말뭉치)를 참고하여 Pretrain(Full Finetuning)된 모델임
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## Intended Uses & Limitations
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The model is designed to assist with healthcare-related queries and tasks. <br>
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However, it should not be used as a substitute for professional medical advice, diagnosis, or treatment.<br>
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Always consult with a qualified healthcare provider for medical concerns.
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이 모델은 Healthcare 관련 질의 및 작업을 지원하도록 설계되었습니다. <br>
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그러나 전문적인 의학적 조언, 진단 또는 치료를 대체하는 데 사용되어서는 안 됩니다. <br>
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의료 관련 문제는 항상 자격을 갖춘 의료 서비스 제공자와 상의하십시오.
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## Training Data
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The model was fine-tuned on a proprietary healthcare dataset. <br>
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Due to privacy concerns, details of the dataset cannot be disclosed.<br>
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wiki, kowiki 데이터 이외<br>
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과학기술정보통신부, 한국지능정보사회진흥원에서 관리하고 있는 AIHub의 <br>
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- 초거대AI 헬스케어 질의응답데이터
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- 한국어 성능이 개선된 초거대 AI 말뭉치
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- 의료, 법률 전문서적 말뭉치
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<br> 등을 활용함
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## Training Procedure
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Full fine-tuning was performed on the base LLaMA 3.1 8B Instruct model using the healthcare dataset.<br>
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Healthcare 데이터 세트를 사용하여 기본 LLaMA 3.1 8B Instruct 모델에서 전체 미세 조정을 수행했습니다.
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## Evaluation Results
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Accuracy by category of mmlu benchmark<br>
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|category| Accuracy|
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|-------------------|--------------|
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|anatomy | 0.68 (92/135)|
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|clinical_knowledge | 0.75 (200/265)|
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|college_medicine | 0.68 (117/173)|
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|medical_genetics | 0.70 (70/100)|
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|professional_medicine | 0.76 (208/272)|
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All Accuracy Mean value: 0.72
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### Use with transformers
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Starting with `transformers >= 4.43.1` onward, you can run conversational inference using the Transformers `pipeline` abstraction or by leveraging the Auto classes with the `generate()` function.
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Make sure to update your transformers installation via `pip install --upgrade transformers`.
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```python
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import transformers
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import torch
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model_id = "unidocs/llama-3.1-8b-komedic-instruct"
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pipeline = transformers.pipeline(
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"text-generation",
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model=model_id,
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model_kwargs={"torch_dtype": torch.bfloat16},
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device_map="auto",
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)
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messages = [
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{"role": "system", "content": "당신은 의료전문가입니다. 질병의 정의, 원인, 증상, 검진, 진단, 치료, 약물, 식이, 생활 측면에서 답변해 주세요"},
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{"role": "user", "content": "공복혈당이 120이상인 경우 제1형 당뇨와 제2형 당뇨 환자는 각각 어떻게 치료를 받아야 하나요?"},
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]
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outputs = pipeline(
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messages,
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max_new_tokens=256,
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)
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print(outputs[0]["generated_text"][-1])
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```
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Note: You can also find detailed recipes on how to use the model locally, with `torch.compile()`, assisted generations, quantised and more at [`huggingface-llama-recipes`](https://github.com/huggingface/huggingface-llama-recipes)
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## Limitations and Bias
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- This model may produce biased or inaccurate results. It should not be solely relied upon for critical healthcare decisions.
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- The model's knowledge is limited to its training data and cut-off date.
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- It may exhibit biases present in the training data.
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- The model may occasionally produce incorrect or inconsistent information.
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- 모델의 지식은 훈련 데이터와 마감일로 제한됩니다.
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- 훈련 데이터에 편향이 있을 수 있습니다.
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- 모델은 가끔 잘못되거나 일관되지 않은 정보를 생성할 수 있습니다.
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- 이 모델은 편향되거나 부정확한 결과를 생성할 수 있습니다. 중요한 의료 결정에 이 모델에만 의존해서는 안 됩니다.
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## Legal Disclaimer
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The model developers and distributors bear no legal responsibility for any consequences arising from the use of this model. <br>
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This includes any direct, indirect, incidental, special, punitive, or consequential damages resulting from the model's output.<br>
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By using this model, users assume all risks that may arise, and the responsibility for verifying and appropriately using the model's output lies solely with the user.<br>
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This model cannot substitute for medical advice, diagnosis, or treatment, and qualified healthcare professionals should always be consulted for medical decisions.<br>
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This disclaimer applies to the maximum extent permitted by applicable law.
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## 법적 책임 면책 조항
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본 모델의 사용으로 인해 발생하는 모든 결과에 대해 모델 개발자 및 배포자는 어떠한 법적 책임도 지지 않습니다. <br>
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이는 모델의 출력으로 인한 직접적, 간접적, 우발적, 특수한, 징벌적 또는 결과적 손해를 포함합니다.<br>
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사용자는 본 모델을 사용함으로써 발생할 수 있는 모든 위험을 감수하며, 모델의 출력에 대한 검증 및 적절한 사용에 대한 책임은 전적으로 사용자에게 있습니다.<br>
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본 모델은 의학적 조언, 진단, 또는 치료를 대체할 수 없으며, 의료 관련 결정을 내릴 때는 반드시 자격을 갖춘 의료 전문가와 상담해야 합니다.<br>
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이 면책 조항은 관련 법률이 허용하는 최대 범위 내에서 적용됩니다.
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## Model Card Contact
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유석 (tobewiseys@unidocs.co.kr), 김진실(kimjs@unidocs.co.kr)
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## Additional Information
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For more details about the base model, please refer to the original LLaMA 3.1 documentation.
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}
|
||||
}
|
||||
23
special_tokens_map.json
Normal file
23
special_tokens_map.json
Normal file
@@ -0,0 +1,23 @@
|
||||
{
|
||||
"bos_token": {
|
||||
"content": "<|begin_of_text|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"eos_token": {
|
||||
"content": "<|eot_id|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"pad_token": {
|
||||
"content": "<|eot_id|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
410563
tokenizer.json
Normal file
410563
tokenizer.json
Normal file
File diff suppressed because it is too large
Load Diff
2065
tokenizer_config.json
Normal file
2065
tokenizer_config.json
Normal file
File diff suppressed because it is too large
Load Diff
Reference in New Issue
Block a user