Google Dev: Local Models & Fine-Tuning
Cloud APIs aren’t the only way to build with AI. Smaller open models can run on a laptop, stay close to your data, and be adapted for a specific job—but only when you make the right tradeoffs.
Join Google Developer Group Tulsa during Tulsa Tech Week for a practical session on local models and fine-tuning. We’ll use Google’s Gemma family as the throughline while exploring:
What can realistically run on a laptop or consumer GPU
How quantization changes memory use, speed, and quality
Fine-tuning versus prompting, retrieval, and tool use
How parameter-efficient methods such as LoRA adapt a model without retraining every weight
How to prepare a small, useful dataset and keep evaluation examples separate
How to compare the base model with the tuned model so “better” means more than a good demo
Where local inference improves privacy, cost, latency, offline access, or control—and where a hosted model is still the better choice
Expect a technical talk, practical demos, honest tradeoffs, and time for questions. You do not need prior machine-learning experience, and you do not need a GPU to follow along.
Plot twist: this is also the September OklahomAI meetup. Google Developer Group Tulsa, OklahomAI, and Techlahoma are bringing the communities together for one shared evening.
Presented as part of Tulsa Tech Week 2026.
Doors and conversation begin at 6:00 PM. The featured program starts at 6:15 PM.
Presenter: Sam Carlton
Live demos will run from Sam’s laptop. Bring your laptop if you want to follow along or test ideas during the session.