Model page

cyankiwi/Qwen3.5-4B-AWQ-4bit pass

No issues found by the checks that have run.

downloads 381.3klikes 25license apache-2.0arch qwen3_5params 4774.6Mupdated 2026-07-21

claims base: Qwen/Qwen3.5-4B · chat template: present · view on Hugging Face ↗

Scan coverageStatic battery2026-08-22Weights battery2026-08-22Behavioral batterynot rundetails
BatteryLooks atStatus
Static batteryMetadata & packagingcomplete 2026-08-22
Weights batteryWeights forensics: no GPU, no downloadcomplete 2026-08-22248,320-token embedding scanned · 0 undertrained · lineage consistent
Behavioral batteryLive-inference differentialsnot run

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

Findings

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

info Embedding-norm glitch scan clean

No undertrained tokens found: every non-special token's embedding norm is above 0.3× the vocabulary median (0.652). The glitch-token data-corruption class has no candidate surface in this model.

info Weights consistent with claimed parent Qwen/Qwen3.5-4B

Mean cosine similarity of 64 sampled token-embedding rows against Qwen/Qwen3.5-4B 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.

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.

Fingerprint

The durable profile of this model: measured weights-and-metadata facts, rebuilt on every scan and battery run. Updated 2026-08-22.

architectureqwen3_5
parameters4774.6M
vocabulary248,320 tokens
licenseapache-2.0
serializationsafetensors
chat templatepresent · sha256:a4aee8afcf2e0711
claimed lineageQwen/Qwen3.5-4B
lineage verifiedconsistent vs Qwen/Qwen3.5-4B — embedding-row cosine 1.000
glitch-token surfaceclean no undertrained tokens
Full measured fingerprint
architecturesQwen3_5ForConditionalGeneration
librarytransformers
pipelineimage-text-to-text
repo files15
revisionef85d23bebab
HF snapshot774.4k downloads · 21 likes · updated 2026-07-21 · captured 2026-08-21
embedding tensormodel.language_model.embed_tokens.weight · BF16 · 248,320×2560
embedding normsmedian 0.652 · mean 0.6558
lineage checkconsistent — cosine 1 over 64 sampled rows vs Qwen/Qwen3.5-4B
Battery runs (1)the run trace behind the findings — what each job measured
batterystatusqueueddurationattempts
weightscomplete2026-08-21 07:4369s1
weights run 2026-08-21 — measurements
probes runglitch-norm-scan, lineage-norm-correlation
embedding tensormodel.language_model.embed_tokens.weight · BF16 · 248,320×2560
glitch surface0 undertrained, 0 plain-ASCII
lineage checkconsistent — cosine 1 over 64 rows vs Qwen/Qwen3.5-4B

Verdict badge

Ship the verdict in your README — it always shows the latest published analysis:

Ingot verdict: pass

[![Ingot scan](https://ingot.tools/api/v1/models/cyankiwi/Qwen3.5-4B-AWQ-4bit/badge.svg)](https://ingot.tools/models/cyankiwi/Qwen3.5-4B-AWQ-4bit)
Gate it in CI