Fine-tuning a 1B Llama model on synthetic endocrinology data improves structured medical note generation and substantially reduces LLM-judged hallucinations and omissions in a browser-based, on-device deployment.
Fine-tuning was performed using PEFT with LoRA adaptation, implemented through the Unsloth library for accelerated training and merging
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Preserving Privacy, Increasing Accessibility, and Reducing Cost: An On-Device Artificial Intelligence Model for Medical Transcription and Note Generation
Fine-tuning a 1B Llama model on synthetic endocrinology data improves structured medical note generation and substantially reduces LLM-judged hallucinations and omissions in a browser-based, on-device deployment.