Qwen/Qwen2.5-VL-3B-Instruct warn
chat template: present · view on Hugging Face ↗
Ingot findings
Static battery: 1 medium finding(s). Deep battery (behavioral differential, glitch-token pass) not yet run. Weights battery: embedding-norm scan over 151936 tokens (BF16, 2048-dim) found 0 undertrained candidates, 0 plain-ASCII. Scanned 2026-08-20 (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.
- With no declared license you have no usage rights by default; treat the weights as all-rights-reserved.
- Open an issue or discussion on the repo asking the owner to declare a license, or use the licensed upstream/parent model instead.
info Embedding-norm glitch scan clean
No undertrained tokens found: every non-special token's embedding norm is above 0.3× the vocabulary median (1.009). The glitch-token data-corruption class has no candidate surface in this model.
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.
- 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.
- 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.
- 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.
Fingerprint
The durable weights-and-metadata profile of this model, rebuilt on every scan and deep-battery run. Updated 2026-08-20.
| architecture | qwen2_5_vl · 36 layers · 2048-dim |
| parameters | 3754.6M |
| vocabulary | 151,936 tokens |
| license | none declared |
| serialization | safetensors |
| chat template | present · sha256:a0bc6f6fc7a29a80 |
| glitch-token surface | clean no undertrained tokens |
Full fingerprint
| architectures | Qwen2_5_VLForConditionalGeneration |
| library | transformers |
| pipeline | image-text-to-text |
| repo files | 14 |
| revision | 66285546d2b8 |
| HF snapshot | 6.5M downloads · 688 likes · updated 2025-04-06 · captured 2026-08-20 |
| embedding tensor | model.embed_tokens.weight · BF16 · 151,936×2048 |
| embedding norms | median 1.0087 · mean 1.0074 |
| lineage check | no claimed base model |
Verdict badge
Ship the verdict in your README — it always shows the latest published analysis:
[](https://ingot.tools/models/Qwen/Qwen2.5-VL-3B-Instruct)