Tagged: fine-tuning
3 articles on fine-tuning.
Fine-Tuning a 70B Model on a Consumer GPU: The Q-LoRA Practical Guide
Q-LoRA + SFTTrainer + Flash Attention v2 means you can fine-tune a 70B parameter model on 24GB of VRAM. Here is what that actually looks like end-to-end, what it costs in quality, and when you should just use the API instead.
EngineeringRead more →
Fine-Tuning LLMs Without the RLHF Headache: The DPO Approach
RLHF is the right idea with the wrong implementation cost for most teams. DPO flips the math — here's how I'd use it to align a healthcare AI model on clinician feedback without burning a month on reward model engineering.
EngineeringRead more →
You Don't Need GPT-4 for That: Small Models and Edge Agents
The assumption that frontier models are required for agentic function calling is wrong — and for healthcare AI, it can also be a compliance liability. Here's when a fine-tuned 7B model is the right architecture, and when it isn't.
EngineeringRead more →