Model page

Qwen/Qwen2.5-Coder-1.5B-Instruct pass

downloads 863.1klikes 137license apache-2.0arch qwen2params 1543.7Mupdated 2025-01-12

claims base: Qwen/Qwen2.5-Coder-1.5B · chat template: present · view on Hugging Face ↗

Scan coverage

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

BatteryLooks atStatus
Static batteryMetadata & packagingcomplete 2026-08-22
Weights batteryWeights forensics — no GPU, no downloadcomplete 2026-08-22151,936-token embedding scanned · 0 undertrained · lineage consistent
Behavioral batteryLive-inference differentialsnot run

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 (0.675). The glitch-token data-corruption class has no candidate surface in this model.

info Weights consistent with claimed parent Qwen/Qwen2.5-Coder-1.5B

Mean cosine similarity of 64 sampled token-embedding rows against Qwen/Qwen2.5-Coder-1.5B is 0.999 — the weights plausibly descend from the declared base (relation: unspecified).

How to fix

Fix or verify the `base_model` declaration so lineage checks can run.

  1. If you own the repo: correct the `base_model` field in the model card metadata to the real, public parent.
  2. If you don't: identify the true parent (config architecture + weight shapes narrow it fast) and re-scan with that lineage in mind.

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 2026-08-22.

architectureqwen2 · 28 layers · 1536-dim
parameters1543.7M
vocabulary151,936 tokens
licenseapache-2.0
serializationsafetensors
chat templatepresent · sha256:cd8e9439f0570856
claimed lineageQwen/Qwen2.5-Coder-1.5B
lineage verifiedconsistent vs Qwen/Qwen2.5-Coder-1.5B — embedding-row cosine 0.999
glitch-token surfaceclean no undertrained tokens
Full measured fingerprint
architecturesQwen2ForCausalLM
librarytransformers
pipelinetext-generation
repo files10
revision2e1fd397ee46
HF snapshot863.1k downloads · 137 likes · updated 2025-01-12 · captured 2026-08-21
embedding tensormodel.embed_tokens.weight · BF16 · 151,936×1536
embedding normsmedian 0.6748 · mean 0.6716
lineage checkconsistent — cosine 0.9994 over 64 sampled rows vs Qwen/Qwen2.5-Coder-1.5B

Battery runs

The run trace behind the findings above: every deep-battery job for this model, with what each run measured or why it failed. Findings are only as good as the runs that produced them.

batterystatusqueueddurationattempts
weightscomplete2026-08-21 07:4344s1
weights run 2026-08-21 measurements
probes runglitch-norm-scan, lineage-norm-correlation
embedding tensormodel.embed_tokens.weight · BF16 · 151,936×1536
glitch surface0 undertrained, 0 plain-ASCII
lineage checkconsistent — cosine 0.9994 over 64 rows vs Qwen/Qwen2.5-Coder-1.5B

Verdict badge

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Ingot verdict: pass

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