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README.md
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---
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license: cc-by-2.0
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language:
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- ar
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- en
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pipeline_tag: text-generation
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tags:
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- Infectious Diseases
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- AceGPT-7B-Chat
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---
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# InfectA-Chat
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To prevent adversial effects of infectious diseases, clear and accessible communication, tracking infectious diseases regularly is crucial. InfectA-Chat is a generative model specifically designed to address this need. Built upon the powerful AceGPT-7B-Chat pre-trained model, InfectA-Chat is fine-tuned to track infectious diseases outbreaks in the infectious diseases domain. This makes it a valuable tool for facilitating communication in both Arabic and English, potentially bridging language barriers and fostering a deeper understanding of infectious diseases.
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# Model Details
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In the fight against infectious diseases in the Middle East, clear and effective communication is paramount. We're excited to announce the release of InfectA-Chat, a generative text model fine-tuned on the AceGPT-7B-Chat model. Designed specifically for the Arabic and English languages, InfectA-Chat excels at following instructions related to infectious disease topics. Notably, our models outperform existing Arabic and state-of-the-art LLMs on Q&A task involving infectious disease instructions while competing with GPT-4. This advancement has the potential to significantly improve communication and disease tracking efforts in the specific region.
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- **Developed by:** Korea Institute of Science and Technology
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- **Language(s) (NLP):** Arabic, English
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- **License:** Creative Commons Attribution 2.0
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- **Finetuned from model [optional]:** AceGPT-7B-Chat
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- **Repository:** KISTI-AI/InfectA-Chat
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# Training Details
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## Training Data
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InfectA-Chat was instruction fine-tuned with 55,400 infectious diseases-related instruction-following data.
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## Training Procedure
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This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure.
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## Training Hyperparameters
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- **Training regime:** fp32 <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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# Evaluation
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## Evaluation Results on Infectious Diseases-related Instruction-Following Dataset
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Experiments on infectious diseases-related instruction-following data and Arabic MMLU benchmark dataset. ‘STEM’, ‘Humanities’, ‘Social Sciences’, ‘Others’ belong to Arabic MMLU.
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## Evaluation Results on Arabic MMLU Benchmark Dataset
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