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abhinand
/
MedEmbed-base-v0.1

sentence-transformers
Safetensors
English
bert
medembed
medical-embedding
clinical-embedding
information-retrieval
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xet
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@@ -43,7 +43,7 @@ This model is intended for use in medical and clinical contexts to improve infor
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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 novel 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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  ![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