Model page

evolveon/Mistral-7B-Instruct-v0.3-abliterated warn

No license declared — no usage rights by default; glitch tokens that can silently corrupt ordinary input.

downloads 187likes 2license none declaredarch mistralparams 7248.0Mupdated 2024-10-14

claims base: mistralai/Mistral-7B-Instruct-v0.3 · chat template: present · view on Hugging Face ↗

Scan coverageStatic battery2026-08-21Weights battery2026-08-21Behavioral batterynot rundetails
BatteryLooks atStatus
Static batteryMetadata & packagingcomplete 2026-08-21
Weights batteryWeights forensics: no GPU, no downloadcomplete 2026-08-2132,768-token embedding scanned · 194 undertrained · lineage consistent
Behavioral batteryLive-inference differentialsnot run

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

Findings

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

medium No license declared

The model card declares no license. You have no usage rights by default — treat as all-rights-reserved until the owner clarifies.

How to fix

Get a license from the owner or pick a licensed alternative — this is a legal gap, not a technical one.

  1. With no declared license you have no usage rights by default; treat the weights as all-rights-reserved.
  2. Open an issue or discussion on the repo asking the owner to declare a license, or use the licensed upstream/parent model instead.

medium Undertrained (glitch) token surface in vocabulary

Embedding-norm scan flagged 194 undertrained tokens (norm < 0.3× the vocabulary median of 0.174), including 10 plain-ASCII strings that can appear in ordinary input as identifiers — e.g. "<0xFB>", "<0xFD>", "<0xFF>", "<0xFA>", "<0xFC>", "<0xFE>", "iNdEx", "febbra". 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-7B-Instruct-v0.3

Mean cosine similarity of 64 sampled token-embedding rows against mistralai/Mistral-7B-Instruct-v0.3 is 1.000 — the weights plausibly descend from the declared base (relation: unspecified).

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

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Fingerprint

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

architecturemistral · 32 layers · 4096-dim
parameters7248.0M
vocabulary32,768 tokens
licensenone declared
serializationsafetensors
chat templatepresent · sha256:e16746b40344d6c5
claimed lineagemistralai/Mistral-7B-Instruct-v0.3
lineage verifiedconsistent vs mistralai/Mistral-7B-Instruct-v0.3 — embedding-row cosine 1.000
glitch-token surface194 undertrained candidates, 10 plain-ASCII
Full measured fingerprint
architecturesMistralForCausalLM
librarytransformers
pipelinetext-generation
repo files13
revision98c57aca142b
HF snapshot386 downloads · 2 likes · updated 2024-10-14 · captured 2026-08-21
embedding tensormodel.embed_tokens.weight · BF16 · 32,768×4096
embedding normsmedian 0.1741 · mean 0.1678
lineage checkconsistent — cosine 0.9999 over 64 sampled rows vs mistralai/Mistral-7B-Instruct-v0.3
glitch-token samples"<0xFB>", "<0xFD>", "<0xFF>", "<0xFA>", "<0xFC>", "<0xFE>", "iNdEx", "febbra", "NdEx", "uitgen"
Battery runs (1)the run trace behind the findings — what each job measured
batterystatusqueueddurationattempts
weightscomplete2026-08-21 05:3251s1
weights run 2026-08-21 — measurements
probes runglitch-norm-scan, lineage-norm-correlation
embedding tensormodel.embed_tokens.weight · BF16 · 32,768×4096
glitch surface194 undertrained, 10 plain-ASCII
lineage checkconsistent — cosine 0.9999 over 64 rows vs mistralai/Mistral-7B-Instruct-v0.3

Verdict badge

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Ingot verdict: warn

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