Fine-Tuning
5 articles about Fine-Tuning from damore.ai: private AI, automation, and Open WebUI guides for small businesses.
When Your Brand's AI Answers Python Questions: Why Scope Control Needs LoRA-Tuned Open-Weight Models
Why off-topic AI answers are a governance failure, and how LoRA fine-tuning on open-weight models gives businesses real control over what their assistant will and will not do.
Training Distinct LLM Voices and Orchestrating Them in a Live Multi-Speaker Pipeline
A technical walkthrough of two open-source projects: a QLoRA fine-tune pipeline that trains 26 distinct personas onto Qwen3-14B, and the Open WebUI pipeline that turns those voices into an orchestrated multi-speaker conversation.
QLoRA vs Full Fine-Tuning: When Does Precision Matter?
A practical guide to choosing between QLoRA and full-precision fine-tuning for domain-specific LLMs. When 4-bit training is the right default — and when it's not.
Building a Clinical Oncology AI: From PubMed Abstracts to a Thinking Medical Model
A deep dive into the end-to-end pipeline for fine-tuning Qwen3 14B into a clinical oncology reasoning model — from synthetic data generation with anti-hallucination safeguards to two-phase SFT + DPO training on NVIDIA DGX Spark.
Unsloth: Training Bigger Models on Smaller Hardware
How Unsloth's pre-quantized models and optimized training toolkit let you fine-tune larger, more capable LLMs on resource-constrained hardware — with a real-world case study on the Cross & Faith AI platform.
Let's find your first three wins
A free 20-minute call. Bring the workflow that annoys you most. I will tell you honestly whether AI fixes it and what the first stage would cost.
Prefer to write first? Send a short inquiry and I reply within one business day.