openai/clip-vit-large-patch14 warn
No license declared — no usage rights by default; glitch tokens that can silently corrupt ordinary input.
chat template: not found · view on Hugging Face ↗
Scan coverageStatic battery2026-08-20Weights battery2026-08-20Behavioral batteryn/adetails
| Battery | Looks at | Status |
|---|---|---|
| Static battery | Metadata & packaging | complete 2026-08-20 |
| Weights battery | Weights forensics: no GPU, no download | complete 2026-08-2049,408-token embedding scanned · 215 undertrained |
| Behavioral battery | Live-inference differentials | n/anot applicable: zero-shot-image-classification model has no text-generation surface to probe |
Ingot runs three batteries against a model. What each one checks →
Findings
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.
medium Undertrained (glitch) token surface in vocabulary
Embedding-norm scan flagged 215 undertrained tokens (norm < 0.3× the vocabulary median of 0.389), including 7 plain-ASCII strings that can appear in ordinary input as identifiers — e.g. "flyeagles", "coscino</w>", "sundaywithmarsha</w>", "instaweather", "mikequind", "pational</w>", "pknot</w>". 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 behavioral 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.
- 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.
Check every checkpoint before it ships
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Fingerprint
The durable profile of this model: measured weights-and-metadata facts, rebuilt on every scan and battery run. Updated 2026-08-20.
| architecture | clip |
| parameters | 427.6M |
| vocabulary | 49,408 tokens |
| license | none declared |
| serialization | safetensors pickle |
| chat template | none |
| glitch-token surface | 215 undertrained candidates, 7 plain-ASCII |
Full measured fingerprint
| architectures | CLIPModel |
| library | transformers |
| pipeline | zero-shot-image-classification |
| repo files | 13 — pickle: pytorch_model.bin |
| revision | 32bd64288804 |
| HF snapshot | 6.3M downloads · 2.1k likes · updated 2023-09-15 · captured 2026-08-20 |
| embedding tensor | text_model.embeddings.token_embedding.weight · F32 · 49,408×768 |
| embedding norms | median 0.3886 · mean 0.3854 |
| lineage check | no claimed base model |
| glitch-token samples | "flyeagles", "coscino</w>", "sundaywithmarsha</w>", "instaweather", "mikequind", "pational</w>", "pknot</w>" |
Battery runs (2)the run trace behind the findings — what each job measured
| battery | status | queued | duration | attempts |
|---|---|---|---|---|
| weights | complete | 2026-08-20 18:02 | 4s | 1 |
| weights | complete | 2026-08-20 08:10 | 5s | 1 |
Verdict badge
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[](https://ingot.tools/models/openai/clip-vit-large-patch14)