GEORGIAN.io
Supported by Render
Builder Series · Season 1 · Episode 1

Fine-Tune & Ship

Fine-tune high-efficiency local models using Georgian’s open-source toolkit, deploy them in one-click on Render, and showcase your production builds to top-tier startups.

$4,000 Render CreditsTeam size: 1–3Any Base Model
The flagship track: the local-first router

A Stanford study found 71.3% of real-world ChatGPT queries could be accurately answered by a small, local model instead of a frontier API. Builders fine-tune and ship the classifier that makes that 71.3% cheap, fast, and private.

Read the paper
hermes-triage · real fine-tune output

$ ollama run hermes-triage

>>> Ticket: Charger cable frayed and sparking. Let me know what you need from me.

Category: Hardware | Priority: High| Reply: Thanks for flagging this — we'll escalate to hardware support and arrange a replacement or repair. Expect an update within 1 business day.

Season trailer drops at kickoff. The output above is real — try it live →

Kickoff DaySeptember 24, 2026
FormatToronto (In-person) & Virtual
Challenge Period8-Week Guided Timeline
Co-hosted & Sponsored by
G
Georgian AI Lab
Render
Vector Institute
Mentors

Behind the Episode

Learn from and build directly with core platform engineers and researchers.

Karan Balaji

Karan Balaji

Co-host

Built this season’s prototype end-to-end — a real LoRA fine-tune, GGUF export pipeline, and Render deployment — for this case study.

Azin Asgarian

Azin Asgarian

AI Technical Lead, Georgian AI Lab

Leads applied AI research with Georgian’s portfolio companies. Has spoken publicly on transfer learning — the model this series is named for.

Paul Inder

Paul Inder

Machine Learning Engineer, Georgian

Builds applied ML systems at Georgian, with prior experience shipping AI-driven products at ideal.com and Ceridian.

Schedule

Kickoff Day Agenda

Kickstart the build window with direct live instructions and workshops.

18:00 - 18:30 EST
Kickoff & Intros

Welcome notes, community alignment, and activation instructions for the $50 Render credit wallets.

18:30 - 19:15 EST
Toolkit Walkthrough

Deep-dive into the LLM Fine-Tuning Toolkit. Pointing at weights, loading dataset slices, and quantization options.

19:15 - 20:00 EST
Render Deploy Demo

One-click blueprints deployment demonstration. Setting up static endpoints and scaling without GPUs.

20:00 - 20:30 EST
Office Hours Setup

Interactive Q&A session, team matching finalization, and booking mentor office hours slot list.

Resources

The Toolkit & Ecosystem

Use verified tools and starter templates to accelerate model optimization and deployment.

Core Tool
Georgian Fine-Tuning Toolkit

A high-performance pipeline for LoRA and QLoRA fine-tuning. Includes preconfigured templates for model quantization, sequence packing, and structured JSON output tasks.

git clone https://github.com/georgian-io/LLM-Finetuning-Toolkit.git
Deployment
Render Hosting Credits

Hosted cloud endpoints for your optimized weights. The official blueprint deploys your model inside an inference worker (like HuggingFace TGI or vLLM) in seconds.

$50 Kickoff VoucherNo GPU Required for Phi-3
Highlights

Event Recap & Gallery

See what builders achieve during the challenge window.

Preview Walkthrough Video

Fine-Tune & Ship Highlight Reel

A synthesis of kickoff day, coding sprint sessions, and Demo Day presentations.

Mockup Photo

Toronto Launch Demo

Builders gathered at the Toronto Hub finalizing dataset formatting files.

Mockup Photo

Final Submission Reviews

Render platform team scoring deployments on criteria of latency and cost.

Launch something. Tag us for a reshare.

Ready to show your model? Publish your Render link and tag our handles to get featured.