Model page

Qwen/Qwen2.5-VL-7B-Instruct warn

downloads 9.6Mlikes 1.7klicense apache-2.0arch qwen2_5_vlparams 8292.2Mupdated 2025-04-06

chat template: present · view on Hugging Face ↗

Ingot findings

Static battery clean: safetensors weights, license declared, no template/tokenizer drift detected. Deep battery not yet run. Weights battery: embedding-norm scan over 152064 tokens (BF16, 3584-dim) found 5768 undertrained candidates, 127 plain-ASCII. Scanned 2026-08-20 (published from a community scan).

medium Undertrained (glitch) token surface in vocabulary

Embedding-norm scan flagged 5768 undertrained tokens (norm < 0.3× the vocabulary median of 0.948), including 127 plain-ASCII strings that can appear in ordinary input as identifiers — e.g. "ForCanBeConverted", "ForCanBeConvertedToF", "PostalCodesNL", "$PostalCodesNL", "<unk>", "(stypy", "useRalative", "TokenNameIdentifier". 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 GPU deep 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.

Fingerprint

The durable weights-and-metadata profile of this model, rebuilt on every scan and deep-battery run. Updated 2026-08-20.

architectureqwen2_5_vl · 28 layers · 3584-dim
parameters8292.2M
vocabulary152,064 tokens
licenseapache-2.0
serializationsafetensors
chat templatepresent · sha256:a0bc6f6fc7a29a80
glitch-token surface5,768 undertrained candidates, 127 plain-ASCII
Full fingerprint
architecturesQwen2_5_VLForConditionalGeneration
librarytransformers
pipelineimage-text-to-text
repo files16
revisioncc594898137f
HF snapshot9.6M downloads · 1.7k likes · updated 2025-04-06 · captured 2026-08-20
embedding tensormodel.embed_tokens.weight · BF16 · 152,064×3584
embedding normsmedian 0.9478 · mean 0.8827
lineage checkno claimed base model
glitch-token samples"ForCanBeConverted", "ForCanBeConvertedToF", "PostalCodesNL", "$PostalCodesNL", "<unk>", "(stypy", "useRalative", "TokenNameIdentifier", "useRal", "thuisontvangst", "NdrFc", "Cumhurba"

Verdict badge

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Ingot verdict: warn

[![Ingot scan](https://ingot.tools/api/v1/models/Qwen/Qwen2.5-VL-7B-Instruct/badge.svg)](https://ingot.tools/models/Qwen/Qwen2.5-VL-7B-Instruct)
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