Identify model provenance, detect derivative lineage, and audit architecture before you deploy. Scan any HuggingFace model in seconds.
No backdoor detection. No security claims. Just architectural truth.
Stage 1 architecture screening is free and unlimited. No credit card required.
We compare against 2,200+ verified architectures across 545 organizations. Identifies fine-tunes, distillations, and repackaged models that config checks miss.
Stage 1 screens architecture configs instantly (free, unlimited). Stage 2 computes five weight-level signals for definitive lineage determination.
Pro plans export SBOM-compatible reports and PDF audit trails with lineage origin, technique provenance, and compliance verdict — ready for governance review.
Stage 1 output is live today. Stage 2 weight analysis shown below is a roadmap preview.
$ modeldna scan poolside/Laguna-XS.2 [INIT] Connecting to ModelAtlas reference database (2,241 models) [SCAN] Fetching config.json... ── STAGE 1: Architectural Screening ────────────────────────── Architecture: LagunaForCausalLM Hidden size: 2048 Vocab size: 100,352 Lineage family: GQA+SWA Hybrid Stage 1 verdict: SIMILAR DESIGN → proceed to Stage 2 ── STAGE 2: Weight-Level DNA Fingerprint ───────────────────── EAS Embedding anchor similarity: 0.12 ▪▪░░░░░░░░ low END Norm distribution: 0.31 ▪▪▪░░░░░░░ low NLF Norm layer fingerprint: 0.28 ▪▪░░░░░░░░ low LEP Layer energy profile: 0.41 ▪▪▪▪░░░░░░ moderate WVC Weight cosine: 0.18 ▪░░░░░░░░░ low ── VERDICT ──────────────────────────────────────────────────── Composite DNA Score: 0.26 / 1.00 Classification: ARCHITECTURAL INSPIRATION (not weight-derived) Lineage: GQA+SWA Hybrid — adopted pattern from StepFun (Feb 2026) Weights: INDEPENDENT — different vocab rules out tokenizer inheritance ✓ No weight inheritance detected Report saved: ./modeldna-report-laguna-xs2.json Powered by ModelAtlas · modeldna.ai · a RadicalNotion product
We parse the model config to identify architecture family, vocab, and technique signatures. Resolves the majority of cases instantly.
FREE · UNLIMITED · <3sFive statistical signals (EAS, END, NLF, LEP, WVC) will analyze weight distributions to detect derivative relationships configs can't reveal.
STAGE 2 · Coming soonComposite DNA score, lineage classification, and optional ModelAtlas enrichment — VRAM estimates, ARS scores, and technique origin chain.
PRO · JSON / PDF / SBOMThe ModelAtlas knowledge engine runs on RadicalNotion infrastructure. You get enterprise-grade depth at a fraction of incumbent pricing.
All scanning is Stage 1 — architecture screening from config.json only. No weight download required. Stage 2 weight-level analysis is on the roadmap.
For anyone using open weights on HuggingFace.
For MLOps and AI platform teams vetting models at scale.
For open weight hosters, compliance teams, and enterprises.
No. modeldna analyzes statistical fingerprints for provenance and derivative lineage. We do not perform security vulnerability scanning or malware detection. These are different problems requiring different tools.
No. Our results are based on statistical fingerprinting — high-confidence evidence of lineage, not cryptographic signatures. Results are suitable for compliance review and audit documentation but not legal disputes over IP ownership.
ModelAtlas continuously scans and indexes public model releases, extracting architecture signatures, technique taxonomies, and lineage relationships. The reference database is private and updated weekly. The CLI queries it via API — you never see the raw database.
Stage 1 works on any model with a config.json. Stage 2 weight analysis requires dequantization to BF16 first — this is handled automatically for supported formats. GGUF Q4/Q8 and safetensors FP8 are supported; AWQ/GPTQ support is in development.