README.md

metadata

title: PixelLock
emoji: 🎨
colorFrom: purple
colorTo: indigo
sdk: docker
app_port: 7860
pinned: true
license: gemma
short_description: Footprint-locked AI pixel-art retexturing
models:
  - solarkyle/pixellock-gemma-12b-pixelart-gguf
tags:
  - gradio
  - build-small-hackathon
  - track:wood
  - sponsor:modal
  - achievement:offbrand
  - achievement:welltuned
  - achievement:llama
  - achievement:sharing
  - achievement:fieldnotes
  - achievement:offgrid
  - best-demo
  - bonus-quest-champion
  - pixel-art

🎨 PixelLock — AI Pixel-Art Retexturing

Upload a sprite, pick a vibe (or write your own), hit Run. PixelLock restyles the colors and shading while keeping the exact silhouette — pixel-perfect, guaranteed by construction.

⚠️ This Space runs on CPU (the hackathon org has no dedicated-GPU credits), so live edits won't run here. ▶ Try it live on GPU → https://huggingface.co/spaces/solarkyle/pixellock (cold-starts ~60s) — or watch the 45-second demo video linked below.

🔗 Links

• 🎥 Demo video: WATCH ▶
• 📣 Social post: SEE POST
• 🧠 Model (fine-tuned GGUF): https://huggingface.co/solarkyle/pixellock-gemma-12b-pixelart-gguf
• 📄 Full technical writeup: read it

The idea: the wrong model on purpose

PixelLock does not use an image generator. It uses a fine-tuned text LLM (Gemma-4-12B). The sprite is serialized to a tiny text wire — a PALETTE block plus a GRID of space-separated cells — and the model rewrites that text in a new style. The trick is a per-sprite GBNF decoding grammar (llama.cpp): every transparent cell is pinned to a fixed literal, so the model is physically incapable of moving a pixel. The footprint and transparency are preserved by construction, not by luck. It's language modeling, not diffusion — and that's exactly why the shape can never break.

In a benchmark, no model could emit a correct 32×32 grid unconstrained (~0/150 attempts); the grammar takes validity from 0% → 100% at every size (16×16 → 128×128, incl. 2× upscale), footprint-perfect every time.

The tech

• Fine-tuned model — QLoRA fine-tune of Gemma-4-12B (trained on Modal, A100-80GB) on a curated corpus of palette-indexed pixel-art sprites (≤64px); completion-only loss, step-checkpointing, final eval loss 0.378. Exported to GGUF (q4_k_m).
• Grammar-constrained decoding — a per-sprite GBNF grammar compiled from the input footprint; the silhouette is locked in the decoder, not post-filtered.
• Custom Gradio UI — a heavily themed gr.Blocks interface (Off-Brand) that builds the grammar per upload, footprint-checks the output, and shows you the raw text the model wrote.
• Serving — Docker GPU Space running llama.cpp llama-server (CUDA) with the per-request grammar; auto-sleeps when idle.

Built for the Build Small hackathon · Thousand Token Wood track.