Brazenle/dom-hotdog-rain

Dom: hotdog-rain training checkpoint

Richard Jones's experimental portfolio assistant, fine-tuned from Qwen2.5-0.5B-Instruct using LoRA. This release preserves the trained adapter from run dom-ui-20260804123828-a9e36621.

Artifact status

The adapter/ directory contains the trained PEFT weights and tokenizer. The root tokenizer/config and onnx/model_q4.onnx contain the merged, 4-bit browser-ready checkpoint. The ONNX file is approximately 770 MB; loading is explicitly opt-in and memory-constrained devices may not support it.

Observed evaluation

The saved pre-export evaluation passed both of these requests:

• Make it rain hotdogs over the portfolio. produced a PAGE_ACTION_JSON call to window.__shoegunDomEffects?.hotdogRain().
• Stop the hotdog rain. produced a PAGE_ACTION_JSON call to window.__shoegunDomEffects?.stopHotdogRain().

The full saved evaluation passed 7 of 29 checks (24.1%). This is an experimental checkpoint, not a reliable general-purpose assistant. These results are from the original adapter evaluation, not an ONNX or browser evaluation.

The merged q4 export separately passed both hotdog-rain requests in Transformers.js CPU inference on September 7, 2026, producing the correct hotdogRain() and stopHotdogRain() calls. This checks learned output directly, without the portfolio's deterministic command shortcut. WebGPU performance and general capabilities are not established by these two checks.

import { pipeline } from '@huggingface/transformers';
const dom = await pipeline('text-generation', 'Brazenle/dom-hotdog-rain', {
  dtype: 'q4', device: 'wasm'
});
// Pin a published commit revision for a production deployment.

Host integration

The model proposes an action; the portfolio implements the animation and executes approved actions. Model weights do not themselves draw hotdogs. The host must validate actions and report actual execution outcomes. Do not execute arbitrary model-generated JavaScript in a privileged context.

Provenance and privacy

Base model: Qwen/Qwen2.5-0.5B-Instruct. LoRA rank 16, alpha 32, dropout 0.05. Only the selected model artifacts are published here. Raw training captures, private datasets, optimizer states, and local environment files are excluded.