I demonstrated a practical proof-of-concept (POC) where I fine-tuned a language model for under $50 to translate complex medical notes into plain, patient-friendly English. By leveraging cost-effective infrastructure and streamlined workflows, I show that effective AI customization no longer requires deep pockets. Techniques like LoRA (Low-Rank Adaptation) put fine-tuning within reach for small teams and budget-conscious projects. like LoRA tuning within reach for small teams and budget-conscious projects.
The piece walks through my step-by-step process—from dataset prep and parameter tuning to deployment—highlighting how affordable compute and smart engineering can deliver patient-centered tools that improve healthcare communication.
Read the post here, access my Colab file here, or view the data and model here.