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README.md
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![synthetic-datagen-flow](https://cdn-uploads.huggingface.co/production/uploads/60c8619d95d852a24572b025/asaA5QDO_j0PWFQV9NXCu.png)
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The model was trained using a
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1. Source: Clinical notes from PubMed Central (PMC)
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2. Processing: LLaMA 2 70B model used to generate query-response pairs
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3. Augmentation: Negative sampling for challenging examples
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![synthetic-datagen-flow](https://cdn-uploads.huggingface.co/production/uploads/60c8619d95d852a24572b025/asaA5QDO_j0PWFQV9NXCu.png)
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The model was trained using a simple yet effective synthetic data generation pipeline:
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1. Source: Clinical notes from PubMed Central (PMC)
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2. Processing: LLaMA 2 70B model used to generate query-response pairs
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3. Augmentation: Negative sampling for challenging examples
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