Model page

Aratako/NemoAurora-RP-12B warn

Its license differs from its base model's; the chat template differs from its base model, which changes behavior; its tokenizer differs from its claimed base model. Plus 1 more issue.

downloads 67likes 2license cc-by-nc-4.0arch mistralparams 12247.8Mupdated 2025-06-08

claims base: mistralai/Mistral-Nemo-Instruct-2407, Aratako/Mistral-Nemo-12B-RP, nothingiisreal/MN-12B-Celeste-V1.9, NeverSleep/Lumimaid-v0.2-12B, ArliAI/Mistral-Nemo-12B-ArliAI-RPMax-v1.2, anthracite-org/magnum-v4-12b, Elizezen/Himeyuri-v0.1-12B · chat template: present · view on Hugging Face ↗

Scan coverageStatic battery2026-08-21Weights battery2026-08-21Behavioral batteryfaileddetails
BatteryLooks atStatus
Static batteryMetadata & packagingcomplete 2026-08-21
Weights batteryWeights forensics: no GPU, no downloadcomplete 2026-08-21131,074-token embedding scanned · 140 undertrained · lineage consistent
Behavioral batteryLive-inference differentialsfailed/api/worker/complete: 500 {"error":"unsupported Unicode escape sequence"}

Ingot runs three batteries against a model. What each one checks →

Findings

Scanned 2026-08-21 · published from a community scan.

medium License differs from claimed parent (cc-by-nc-4.0 vs apache-2.0)

This model declares cc-by-nc-4.0 while its claimed base mistralai/Mistral-Nemo-Instruct-2407 declares apache-2.0. Verify the re-license is permitted before commercial use.

How to fix

Verify the re-license is actually permitted before relying on it.

  1. Read the parent's license for derivative-work and re-licensing terms — many open-weight licenses (e.g. Llama-family) do not permit arbitrary re-licensing.
  2. If the re-license is not permitted, the parent's terms govern your use regardless of what this repo declares.

medium Chat template differs from claimed parent

The chat template does not match mistralai/Mistral-Nemo-Instruct-2407's. Template drift silently changes model behavior even when weights are identical — 37% of drifted derivatives in our census left it undisclosed. Diff the templates before deploying.

How to fixingot patch

Restore the parent's chat template in `tokenizer_config.json` — a pure metadata fix.

  1. Run `ingot patch <owner/model>` — the patch manifest carries the parent's template and applies it to a local copy's `tokenizer_config.json`.
  2. Or fix by hand: copy the `chat_template` value from the parent repo's `tokenizer_config.json` into this model's, and pin your serving stack to that file.
  3. If the drift was intentional (the author retrained on a new template), confirm that in the model card before "fixing" it — restoring the parent template on retrained weights changes behavior too.

medium Vocabulary size differs from claimed parent (131074 vs 131072)

A changed vocab means changed tokenization: strings will split differently than on mistralai/Mistral-Nemo-Instruct-2407, which can shift behavior on identifiers, codes, and non-English text.

How to fixweight-level

Not patchable: the vocab size mirrors the embedding matrix in the weights. Verify the change was intentional.

  1. Do not edit `vocab_size` in config.json to "match the parent" — it must equal the embedding table in the shipped weights or the model won't load.
  2. Diff the tokenizers (`tokenizer.json` / added_tokens) against the parent to see what was added or removed, and test your own identifiers, codes, and non-English text through both.
  3. If the drift is unexplained by the model card, treat tokenization-sensitive behavior as unvalidated on this model.

medium Undertrained (glitch) token surface in vocabulary

Embedding-norm scan flagged 140 undertrained tokens (norm < 0.3× the vocabulary median of 0.641), including 24 plain-ASCII strings that can appear in ordinary input as identifiers — e.g. "erresident", "abezian", "komert", "higiez", "pemerint", "banako", "komertzio", "tanleria". In models where this class was tested behaviorally, such tokens silently rewrote user input into confident, schema-valid, wrong output. These are candidates from the weights alone; behavioral confirmation requires the behavioral battery.

How to fixruntime guardweight-level

Keep the affected token strings out of the model's input — the scan-derived runtime guard carries this model's exact blocklist.

  1. Fetch this model's guard artifact (`/api/v1/guard/<owner>/<model>`): the confirmed corrupting tokens and the low-norm candidate list, derived from the published scan.
  2. Screen inbound text with it (the `@ingotai/guard` package is a reference implementation) and route flagged records to a different model or human review — verbatim-copy tasks on flagged strings are the failure mode.
  3. The underlying cause is undertrained embeddings in the weights; a true fix is weight-level (continued pretraining on the affected tokens) — that is not a patch, it's a training job.

info Weights consistent with claimed parent mistralai/Mistral-Nemo-Instruct-2407

Mean cosine similarity of 64 sampled token-embedding rows against mistralai/Mistral-Nemo-Instruct-2407 is 0.973 — the weights plausibly descend from the declared base (relation: unspecified).

Put this result in your workflow

Check every checkpoint before it ships

Use the web app, API, CLI, or CI gate to scan candidate checkpoints and catch model drift before deployment. Public-model scans publish to the open database; paid plans add the volume needed for continuous checks.

Fix it

Some findings are metadata-level and patchable — apply the fixes to your local copy (your weights never leave your machine):

npx @ingotai/scan patch Aratako/NemoAurora-RP-12B

Remediation guidance addresses the documented findings only. It is evidence-driven repair, not a safety certification of the model.

Fingerprint

The durable profile of this model: measured weights-and-metadata facts, rebuilt on every scan and battery run. Updated 2026-08-21.

architecturemistral · 40 layers · 5120-dim
parameters12247.8M
vocabulary131,074 tokens
licensecc-by-nc-4.0
serializationsafetensors
chat templatepresent · sha256:ad407b4128ca10f1
claimed lineagemistralai/Mistral-Nemo-Instruct-2407, Aratako/Mistral-Nemo-12B-RP, nothingiisreal/MN-12B-Celeste-V1.9, NeverSleep/Lumimaid-v0.2-12B, ArliAI/Mistral-Nemo-12B-ArliAI-RPMax-v1.2, anthracite-org/magnum-v4-12b, Elizezen/Himeyuri-v0.1-12B
lineage verifiedconsistent vs mistralai/Mistral-Nemo-Instruct-2407 — embedding-row cosine 0.973
glitch-token surface140 undertrained candidates, 24 plain-ASCII
Full measured fingerprint
architecturesMistralForCausalLM
librarytransformers
pipelinetext-generation
repo files14
revision21f09989fc31
HF snapshot292 downloads · 2 likes · updated 2025-06-08 · captured 2026-08-21
embedding tensormodel.embed_tokens.weight · BF16 · 131,074×5120
embedding normsmedian 0.6414 · mean 0.6173
lineage checkconsistent — cosine 0.9733 over 64 sampled rows vs mistralai/Mistral-Nemo-Instruct-2407
glitch-token samples"erresident", "abezian", "komert", "higiez", "pemerint", "banako", "komertzio", "tanleria", "igelts", "miejs", "-usti", "zimendu"
Battery runs (1)the run trace behind the findings — what each job measured
batterystatusqueueddurationattempts
weightscomplete2026-08-21 05:162m1
weights run 2026-08-21 — measurements
probes runglitch-norm-scan, lineage-norm-correlation
embedding tensormodel.embed_tokens.weight · BF16 · 131,074×5120
glitch surface140 undertrained, 24 plain-ASCII
lineage checkconsistent — cosine 0.9733 over 64 rows vs mistralai/Mistral-Nemo-Instruct-2407

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Ingot verdict: warn

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