Advanced LoRA Techniques: Multi-LoRA, LoRA+, and Beyond

Last year, I fine-tuned a 7B parameter model with standard LoRA. It worked, but accuracy was 5% lower than full fine-tuning. After experimenting with Multi-LoRA, LoRA+, and advanced techniques, I’ve achieved 98% of full fine-tuning performance with 1% of the parameters. Here’s everything you need to know about advanced LoRA techniques. Figure 1: LoRA Techniques […]

Read more โ†’

EMR Modernization: Migrating from Legacy HL7 v2 to FHIR

Executive Summary Migrating from HL7 v2 to FHIR is one of the most critical modernization challenges facing healthcare IT. With billions of HL7 v2 messages processed daily across hospital EMRs, the transition requires careful planning using proven patterns like Strangler Fig, FHIR Facade, and Dual-Write strategies. ๐Ÿฅ HEALTHCARE INTEROPERABILITY SERIES This article is part of […]

Read more โ†’

LLM Fine-Tuning Techniques: From LoRA to Full Parameter Training

Introduction: Fine-tuning transforms general-purpose LLMs into specialized models that excel at your specific tasks. While prompting can get you far, fine-tuning unlocks capabilities that prompting alone cannot achieve: consistent output formats, domain-specific knowledge, reduced latency from shorter prompts, and behavior that would require extensive few-shot examples. This guide covers the practical aspects of LLM fine-tuning: […]

Read more โ†’