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README.md
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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
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3. Augmentation: Negative sampling for challenging examples
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4. Format: Triplets (query, positive response, negative response) for contrastive learning
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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 3.1 70B](https://huggingface.co/meta-llama/Llama-3.1-70B-Instruct) model used to generate query-response pairs
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3. Augmentation: Negative sampling for challenging examples
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4. Format: Triplets (query, positive response, negative response) for contrastive learning
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