microsoft/deberta-base warn
Weights only ship in a format that can run code when loaded.
chat template: not found · view on Hugging Face ↗
Scan coverageStatic battery2026-08-25Weights battery2026-08-25Behavioral batteryn/adetails
| Battery | Looks at | Status |
|---|---|---|
| Static battery | Metadata & packaging | complete 2026-08-25 |
| Weights battery | Weights forensics — no GPU, no download | complete 2026-08-2550,265-token embedding scanned · 0 undertrained · pickle audit clean |
| Behavioral battery | Live-inference differentials | n/anot applicable — fill-mask model has no text-generation surface to probe |
Ingot runs three batteries against a model. What each one checks →
Findings
Scanned 2026-08-25 · published from a community scan.
medium Pickle-serialized weights, no safetensors
Weights ship only as pickle-based files (bpe_encoder.bin, pytorch_model.bin). Loading pickle executes arbitrary code from the file — prefer a safetensors release or load in a sandbox.
How to fix
Convert the weights to safetensors before loading them anywhere that matters.
- Do not load the pickle files in-process — pickle deserialization executes arbitrary code from the file.
- Convert locally in a sandbox: `pip install safetensors` and use `safetensors.torch.save_file` on a state dict loaded with `torch.load(..., weights_only=True)` (refuses most code-execution payloads), or use Hugging Face's `convert.py` space/script.
- Pin the exact revision hash you converted from, and load only your converted safetensors artifact from then on.
info Partial coverage — not a generative language model
fill-mask model — no generation surface, so behavioral (live-inference) checks are not applicable; packaging, license, and weights forensics apply.
info Embedding-norm glitch scan clean
No undertrained tokens found: every non-special token's embedding norm is above 0.3× the vocabulary median (1.268). The glitch-token data-corruption class has no candidate surface in this model.
info Pickle static analysis clean
Opcode-level parse of pytorch_model.bin, bpe_encoder.bin (no code executed) found only standard serialization globals (3 distinct, all torch/collections/numpy). Pickle remains an executable format — this verifies the current bytes, not future uploads; prefer a safetensors release.
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 2026-08-25.
| architecture | deberta · 12 layers · 768-dim |
| vocabulary | 50,265 tokens |
| license | mit |
| serialization | no safetensors pickle |
| chat template | none |
| glitch-token surface | clean no undertrained tokens |
Full measured fingerprint
| library | transformers |
| pipeline | fill-mask |
| repo files | 10 — pickle: bpe_encoder.bin, pytorch_model.bin |
| revision | 0d1b43ccf21b |
| HF snapshot | 403.4k downloads · 85 likes · updated 2022-09-26 · captured 2026-08-25 |
| pickle audit | pytorch_model.bin, bpe_encoder.bin — 3 standard global(s) · legacy (pre-1.6) format, head-scan only |
| embedding tensor | deberta.embeddings.word_embeddings.weight · F32 · 50,265×768 |
| embedding norms | median 1.2677 · mean 1.2708 |
| lineage check | no claimed base model |
Battery runs (1)the run trace behind the findings — what each job measured
| battery | status | queued | duration | attempts |
|---|---|---|---|---|
| weights | complete | 2026-08-25 20:26 | 21s | 1 |
weights run 2026-08-25 — measurements
| probes run | glitch-norm-scan, zero-template-token-scan, pickle-static-analysis, lineage-norm-correlation |
| probes skipped | token-decode: no tokenizer.json |
| embedding tensor | deberta.embeddings.word_embeddings.weight · F32 · 50,265×768 |
| glitch surface | 0 undertrained, 0 plain-ASCII |
| lineage check | not checked (no claimed base model) |
Verdict badge
Ship the verdict in your README — it always shows the latest published analysis:
[](https://ingot.tools/models/microsoft/deberta-base)