Project lanes
Open Day experiences
Visitor-ready experiments that make tokens, computer vision, speech, cybersecurity, and human oversight visible enough to discuss.
Local-first AI systems and public demos
Run it. Teach it. Inspect it.
Crunchy Codes is my public workshop for Open Day experiences, local model infrastructure, and practical tools that make AI systems easier to explain, operate, and trust.
idea
build
ship
Open Day
Public demos
Local AI
Model runtime
Desktop
Practical tools
Who am I
Dr Jason Holdsworth
I build practical local-first tools.
I'm Dr Jason Holdsworth, a Digital Technology academic and educator at James Cook University, and the maker behind Crunchy Codes. My work sits around local-first software, practical AI tools, public teaching demos, and human-AI interaction experiments.
Now building
Recent public work.
- Cybersecurity Challenge and SpeechShift Open Day experiences
- SceneChat local camera, detector, and scene-description pipeline
- ModelDeck local runtime manager and stable capability gateway
- Crowd AI, Text Diffusion Lab, and TokenTrail public demos
- Self-contained DiffusionGemma GPTQ Q4 g32 model published on Hugging Face
Projects
Recent public portfolio.
The latest repositories form a connected local-first lab: public experiences for teaching AI, shared infrastructure for running models, and practical tools for the machines hosting them.
Project lanes
Local AI infrastructure
A shared runtime manager, stable capability gateway, local model clients, and explicit offline fallbacks for dependable demos.
Project lanes
Practical desktop tools
Focused GNOME, macOS, VS Code, and desktop tools for inspecting local state and keeping everyday workflows understandable.
Active build / local runtime infrastructure
ModelDeck
A runtime manager and stable capability gateway for local AI on the Framework Desktop. It turns pinned model snapshots into explicitly managed workers and publishes versioned routes for a coordinated suite of public demos.
Open Day demo / local computer vision
SceneChat
A local-first camera experience that keeps fast object detection separate from periodic multimodal scene descriptions. It includes explicit privacy controls, reset behaviour, staff diagnostics, and replay operation when the live model is unavailable.
Replay-first MVP / local speech
SpeechShift
An honest speech-transformation demo with prepared local voice and language shifts, plus an opt-in, memory-only microphone path. Its local DSP baseline transforms captured audio without pretending to recognise or translate the visitor's words.
Published model / GPTQ Q4 g32 + BF16 hybrid
DiffusionGemma Q4 for ModelDeck
A self-contained quantised variant of DiffusionGemma 26B built for local text diffusion on AMD ROCm. Expert projections use GPTQ Q4 g32 while non-expert tensors remain BF16, with offline loading, release checksums, and comparative quality evidence.
Open Day demo / staged text refinement
Text Diffusion Lab
A public explanation of generation by iterative refinement rather than next-token prediction. The visitor experience has a reliable scripted path, while staff can run the published DiffusionGemma Q4 variant through ModelDeck's native diffusion API.
Active build / cybersecurity awareness
Can You Spot the Scam?
A local-first game where visitors investigate fictional messages, flag warning signs, choose safe responses, and solve approachable cipher cases with concise educational feedback.
MVP 0.2 / human oversight demo
Humans in the Loop
A QR phone-to-screen experience where a crowd sets goals and rules, reviews a deterministic AI-style proposal, and decides when to accept, repair, seek evidence, or involve a person.
Open Day demo / token-level generation
TokenTrail
A replayable teaching demo that exposes prompt tokens, candidate probabilities, and generated text one step at a time using local Hugging Face traces or prepared scripted fallbacks.
Research MVP / local voice conversation
Repartee
An interruptible voice-conversation experiment where a weak local speech layer owns timing and bounded replies, then escalates more substantive requests to ModelDeck through the same output path.
GNOME extension / Framework Desktop
System Usage Monitor
A Fedora 44 top-bar monitor for RAM, storage, temperature, and fan readings, with configurable local JSONL sensor history and Framework Desktop-friendly labels.
Desktop app and CLI / model library
HuggingFacePull
A local FastAPI, Electron, and command-line tool for finding, queueing, downloading, and cleaning up Hugging Face model snapshots, including resumable low-concurrency transfers.
Local-first principles
Tools should explain themselves.
Recent Crunchy Codes projects favour explicit user control: local files over hidden services, recoverable downloads over silent failure, and privacy-safe metadata over unnecessary telemetry.
Stay close to the user
Read local state directly, keep sensitive content on-device, and avoid network calls unless the tool genuinely needs them.
Make progress recoverable
Large downloads, long chats, and local experiments should preserve work instead of forcing people to start over.
Keep the controls visible
Prefer plain commands, clear status, and inspectable behaviour over magic that leaves the user guessing.
Contact
Questions, bugs, and project support
For project support, feature ideas, bug reports, or security concerns, use the support page or the issue tracker linked from the relevant project.