Qwen/Qwen2.5-Math-1.5B warn
claims base: Qwen/Qwen2.5-1.5B · chat template: present · view on Hugging Face ↗
Scan coverage
Ingot runs three batteries against a model. What each one checks →
| Battery | Looks at | Status |
|---|---|---|
| Static battery | Metadata & packaging | complete 2026-08-22 |
| Weights battery | Weights forensics — no GPU, no download | complete 2026-08-22151,936-token embedding scanned · 0 undertrained · lineage inconsistent |
| Behavioral battery | Live-inference differentials | not run |
Findings
Scanned 2026-08-22 · published from a community scan.
medium Chat template differs from claimed parent
The chat template does not match Qwen/Qwen2.5-1.5B'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.
- Run `ingot patch <owner/model>` — the patch manifest carries the parent's template and applies it to a local copy's `tokenizer_config.json`.
- 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.
- 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.
info Embedding-norm glitch scan clean
No undertrained tokens found: every non-special token's embedding norm is above 0.3× the vocabulary median (1.187). The glitch-token data-corruption class has no candidate surface in this model.
low Weights diverge from claimed parent Qwen/Qwen2.5-1.5B
This model declares Qwen/Qwen2.5-1.5B as its base (relation: unspecified), but mean cosine similarity of 64 sampled token-embedding rows against that parent is only 0.225 (true finetunes, merges, and quantizations sit above 0.8; independently trained weights sit near 0). Either the lineage label is wrong, or the model was so heavily re-trained, pruned, or distilled that the parent's properties (safety posture, evaluated behavior, licensing basis) should not be assumed to carry over. Verify provenance before relying on the parent's reputation.
How to fix
Fix or verify the `base_model` declaration so lineage checks can run.
- If you own the repo: correct the `base_model` field in the model card metadata to the real, public parent.
- 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.
| architecture | qwen2 · 28 layers · 1536-dim |
| parameters | 1543.7M |
| vocabulary | 151,936 tokens |
| license | apache-2.0 |
| serialization | safetensors |
| chat template | present · sha256:c564d12c9977b894 |
| claimed lineage | Qwen/Qwen2.5-1.5B |
| lineage verified | inconsistent vs Qwen/Qwen2.5-1.5B — embedding-row cosine 0.225 |
| glitch-token surface | clean no undertrained tokens |
Full measured fingerprint
| architectures | Qwen2ForCausalLM |
| library | transformers |
| pipeline | text-generation |
| repo files | 10 |
| revision | 4a83ca6e4526 |
| HF snapshot | 813.0k downloads · 111 likes · updated 2024-09-23 · captured 2026-08-21 |
| embedding tensor | model.embed_tokens.weight · BF16 · 151,936×1536 |
| embedding norms | median 1.1865 · mean 1.1599 |
| lineage check | inconsistent — cosine 0.2253 over 64 sampled rows vs Qwen/Qwen2.5-1.5B |
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.
| battery | status | queued | duration | attempts |
|---|---|---|---|---|
| weights | complete | 2026-08-21 07:43 | 42s | 1 |
weights run 2026-08-21 — measurements
| probes run | glitch-norm-scan, lineage-norm-correlation |
| embedding tensor | model.embed_tokens.weight · BF16 · 151,936×1536 |
| glitch surface | 0 undertrained, 0 plain-ASCII |
| lineage check | inconsistent — cosine 0.2253 over 64 rows vs Qwen/Qwen2.5-1.5B |
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 Qwen/Qwen2.5-Math-1.5B
Remediation guidance addresses the documented findings only. It is evidence-driven repair, not a safety certification of the model.
Verdict badge
Ship the verdict in your README — it always shows the latest published analysis:
[](https://ingot.tools/models/Qwen/Qwen2.5-Math-1.5B)