Model page

Qwen/Qwen3-32B warn

Glitch tokens that can silently corrupt ordinary input.

downloads 3.7Mlikes 754license apache-2.0arch qwen3params 32762.1Mupdated 2025-07-26

chat template: present · view on Hugging Face ↗

Scan coverageStatic battery2026-08-22Weights battery2026-08-22Behavioral batteryfaileddetails
BatteryLooks atStatus
Static batteryMetadata & packagingcomplete 2026-08-22
Weights batteryWeights forensics: no GPU, no downloadcomplete 2026-08-22151,936-token embedding scanned · 3195 undertrained
Behavioral batteryLive-inference differentialsfailedTraceback (most recent call last): | raise HTTPStatusError(message, request=request, response=self) | httpx.HTTPStatusError: Client error '429 Too Many Requests' for url 'https://huggingface.co/api/models/Qwen/Qwen3-32B' | Traceback (most recent call last): | raise _format(HfHubHTTPError, message, response) from e | huggingface_hub.errors.HfHubHTTPError: (Request ID: Root=1-6a8e164f-0718f781578ab1ce3b7b8758;29ee26fb-fb90-4ee7-bcd0-23895f2aafb7)

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

Findings

Scanned 2026-08-22 · published from a community scan.

medium Undertrained (glitch) token surface in vocabulary

Embedding-norm scan flagged 3195 undertrained tokens (norm < 0.3× the vocabulary median of 1.336), including 113 plain-ASCII strings that can appear in ordinary input as identifiers — e.g. "$PostalCodesNL", "ForCanBeConvertedToF", "PostalCodesNL", "ForCanBeConverted", "useRalative", "useRal", "thuisontvangst", "webElementX". 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.

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 2026-08-22.

architectureqwen3 · 64 layers · 5120-dim
parameters32762.1M
vocabulary151,936 tokens
licenseapache-2.0
serializationsafetensors
chat templatepresent · sha256:a55ee1b1660128b7
glitch-token surface3,195 undertrained candidates, 113 plain-ASCII
Full measured fingerprint
architecturesQwen3ForCausalLM
librarytransformers
pipelinetext-generation
repo files27
revision9216db5781bf
HF snapshot3.6M downloads · 736 likes · updated 2025-07-26 · captured 2026-08-21
embedding tensormodel.embed_tokens.weight · BF16 · 151,936×5120
embedding normsmedian 1.3365 · mean 1.2745
lineage checkno claimed base model
glitch-token samples"$PostalCodesNL", "ForCanBeConvertedToF", "PostalCodesNL", "ForCanBeConverted", "useRalative", "useRal", "thuisontvangst", "webElementX", "sexkontakte", "wannonce", "swingerclub", "sextreffen"
Battery runs (2)the run trace behind the findings — what each job measured
batterystatusqueueddurationattempts
gpucomplete2026-08-22 00:415m1
weightscomplete2026-08-21 07:4232s1
gpu run 2026-08-22 — measurements
probes runglitch
weights run 2026-08-21 — measurements
probes runglitch-norm-scan, lineage-norm-correlation
embedding tensormodel.embed_tokens.weight · BF16 · 151,936×5120
glitch surface3,195 undertrained, 113 plain-ASCII
lineage checknot checked (no claimed base model)

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Ingot verdict: warn

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