google-bert/bert-base-uncased pass
chat template: not in config · 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 30522 tokens (F32, 768-dim) found 0 undertrained candidates, 0 plain-ASCII. Scanned 2026-08-20 (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 (1.401). 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 | bert · 12 layers · 768-dim |
| parameters | 110.1M |
| vocabulary | 30,522 tokens |
| license | apache-2.0 |
| serialization | safetensors pickle |
| chat template | none |
| glitch-token surface | clean no undertrained tokens |
Full fingerprint
| architectures | BertForMaskedLM |
| library | transformers |
| pipeline | fill-mask |
| repo files | 16 — pickle: coreml/fill-mask/float32_model.mlpackage/Data/com.apple.CoreML/weights/weight.bin, pytorch_model.bin |
| revision | 86b5e0934494 |
| HF snapshot | 105.4M downloads · 2.7k likes · updated 2024-02-19 · captured 2026-08-20 |
| embedding tensor | bert.embeddings.word_embeddings.weight · F32 · 30,522×768 |
| embedding norms | median 1.4007 · mean 1.4014 |
| lineage check | no claimed base model |
Verdict badge
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[](https://ingot.tools/models/google-bert/bert-base-uncased)