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README.md
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## Introduction
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Aquila is a large language model
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## Model Details
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The
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![pipeline](./img/pipeline.png)
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## Evaluation
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![pipeline](./img/eval-result.jpeg)
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## usage
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```python
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If you find our work helpful, feel free to give us a cite.
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```
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@article{
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title={
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year={2024}
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}
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```
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## Introduction
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Aquila is a large language model independently developed by BAAI. Building upon the Aquila model, we continued pre-training, SFT (Supervised Fine-Tuning), and RL (Reinforcement Learning) through a multi-stage training process, ultimately resulting in the AquilaMed-RL model. This model possesses professional capabilities in the medical field and demonstrates a significant win rate when evaluated against annotated data using the GPT-4 model. The AquilaMed-RL model can perform medical triage, medication inquiries, and general Q&A. We will open-source the SFT data and RL data required for training the model. Additionally, we will release a technical report detailing our methods in developing the model for the medical field, thereby promoting the development of the open-source community.
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## Model Details
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The training process of the model is described as follows. For more information, please refer to our technical report. https://github.com/FlagAI-Open/industry-application/blob/main/Aquila_med_tech-report.pdf
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![pipeline](./img/pipeline.png)
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## Evaluation
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Using GPT-4 for evaluation, the win rates of our model compared to the reference answers in the annotated validation dataset are as follows.
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![pipeline](./img/eval-result.jpeg)
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## usage
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Once you have downloaded the model locally, you can use the following code for inference.
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```python
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If you find our work helpful, feel free to give us a cite.
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```
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@article{Aqulia-Med LLM,
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title={Aqulia-Med LLM: Pioneering Full-Process Open-Source Medical Language Models},
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year={2024}
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}
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```
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