Scan a model, read the report.
ModelDNA Stage 1 runs on a public HuggingFace Space. There's no install, no signup, and no SDK to learn. Paste a model ID, wait a few seconds, copy the JSON.
Try it
The scanner runs on a HuggingFace Space. HuggingFace blocks iframe embedding for security, so it opens in a new tab.
Paste any public HuggingFace model ID, get a Stage 1 verdict in a few seconds. Free, no signup.
What you send
A HuggingFace model identifier. That's it. Formats accepted:
<org>/<model>— e.g.meta-llama/Llama-3.2-1B- Full URL — e.g.
https://huggingface.co/Qwen/Qwen3-4B
The scanner fetches the model's config.json (a few KB), compares it against the ModelAtlas reference corpus, and emits a verdict. Weights are not downloaded for Stage 1.
What you get back
A JSON report. Below is an annotated example; field names are stable and safe to depend on.
{
"model": "poolside/Laguna-XS.2",
"scanned_at": "2026-05-25T17:08:40Z",
"stage": 1,
// architectural fingerprint pulled straight from config.json
"architecture": {
"class": "LagunaForCausalLM",
"hidden_size": 2048,
"vocab_size": 100352,
"family": "GQA+SWA Hybrid"
},
// closest matches in the ModelAtlas reference corpus
"matches": [
{ "model": "StepFun/Step-Audio-2", "score": 0.82 },
{ "model": "Qwen/Qwen3-4B", "score": 0.71 }
],
// verdict — the field you should read first
"verdict": {
"classification": "ARCHITECTURAL_INSPIRATION",
"confidence": "high",
"lineage": "GQA+SWA Hybrid — pattern adopted from StepFun (Feb 2026)",
"next_step": "stage_2_recommended"
}
}Classification values
- INDEPENDENT — no meaningful architectural similarity to known models.
- ARCHITECTURAL_INSPIRATION — adopts a recognizable design pattern (GQA, SWA, MoE routing shape, etc.) without weight inheritance.
- DERIVATIVE_CANDIDATE — config is close enough to a known model that Stage 2 weight analysis is recommended before drawing conclusions.
- CONFIRMED_DERIVATIVE — Stage 2 only. Weight-level signals indicate the model is fine-tuned, distilled, or repackaged from a specific upstream.
What it can't tell you
- Whether the model contains backdoors or malicious weights. That's a different problem with different tooling.
- Cryptographic proof of ownership. Lineage scores are statistical, not legal evidence.
- Anything about private models you haven't made public on HuggingFace. Contact us for on-premise deployment (tim@radicalnotion.ai).
REST API
A versioned POST /v1/scan endpoint ships with the Pro plan. Same JSON shape as above, plus bulk scanning and webhook notifications when known derivatives of your models appear on HuggingFace. Email tim@radicalnotion.ai for early access.