amitayusht/ProofWala-Coq warn
Weights only ship in a format that can run code when loaded; its license differs from its base model's.
claims base: Salesforce/codet5-base · chat template: not found · view on Hugging Face ↗
Scan coverageStatic battery2026-08-25Weights batteryqueuedBehavioral batterynot rundetails
| Battery | Looks at | Status |
|---|---|---|
| Static battery | Metadata & packaging | complete 2026-08-25 |
| Weights battery | Weights forensics — no GPU, no download | queued |
| Behavioral battery | Live-inference differentials | not run |
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 (optimizer.pt, pytorch_model.bin, rng_state_0.pth, …). 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.
medium License differs from claimed parent (mit vs apache-2.0)
This model declares mit while its claimed base Salesforce/codet5-base declares apache-2.0. Verify the re-license is permitted before commercial use.
How to fix
Verify the re-license is actually permitted before relying on it.
- Read the parent's license for derivative-work and re-licensing terms — many open-weight licenses (e.g. Llama-family) do not permit arbitrary re-licensing.
- If the re-license is not permitted, the parent's terms govern your use regardless of what this repo declares.
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 | t5 · 12 layers · 768-dim |
| vocabulary | 32,100 tokens |
| license | mit |
| serialization | no safetensors pickle |
| chat template | none |
| claimed lineage | Salesforce/codet5-base |
| lineage verified | unverified — weights battery pending |
Full measured fingerprint
| architectures | T5ForConditionalGeneration |
| pipeline | text-generation |
| repo files | 31 — pickle: optimizer.pt, pytorch_model.bin, rng_state_0.pth, rng_state_1.pth, rng_state_10.pth, rng_state_11.pth, rng_state_12.pth, rng_state_13.pth, rng_state_14.pth, rng_state_15.pth |
| revision | 7c15213a90d3 |
| HF snapshot | 17 downloads · 0 likes · updated 2025-02-09 · captured 2026-08-25 |
Battery runs (1)the run trace behind the findings — what each job measured
| battery | status | queued | duration | attempts |
|---|---|---|---|---|
| weights | queued | 2026-08-25 22:19 | — | 0 |
Verdict badge
Ship the verdict in your README — it always shows the latest published analysis:
[](https://ingot.tools/models/amitayusht/ProofWala-Coq)