anemll/anemll-gemma-3-270m-it-MONO-ctx512-lut6 warn
Weights only ship in a format that can run code when loaded; loading it runs custom code from the repo; its license differs from its base model's. Plus 1 more issue.
Could not load this model from the Hugging Face API (private, gated, or nonexistent). Findings below are from our archive.
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 (gemma3_monolithic_full_lut6.mlmodelc/analytics/coremldata.bin, gemma3_monolithic_full_lut6.mlmodelc/coremldata.bin, gemma3_monolithic_full_lut6.mlmodelc/weights/weight.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.
medium Repo ships executable Python (trust_remote_code)
The repository contains custom code files that run in-process when loaded with trust_remote_code=True. Pin the revision hash and review the code before loading.
How to fix
Review and pin the custom code; never float on `main` with trust_remote_code=True.
- Read every `.py` file in the repo before first load — this code runs in your process.
- Pin the revision: `from_pretrained(model_id, revision="<commit sha>", trust_remote_code=True)` so a later push can't swap the code under you.
- Prefer a version of the architecture already in `transformers` if one exists, which removes the remote-code requirement entirely.
medium License differs from claimed parent (mit vs gemma)
This model declares mit while its claimed base google/gemma-3-270m-it declares gemma. 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.
medium Architecture differs from claimed parent (gemma vs gemma3_text)
This model declares google/gemma-3-270m-it as its base, but its config declares architecture 'gemma' while the parent is 'gemma3_text'. A finetune, merge, or quantization cannot change the architecture family — the lineage label is wrong or misleading, so treat provenance claims (training data, safety posture, licensing) as unverified.
How to fix
Fix or verify the `base_model` declaration so lineage checks can run.
- If you own the repo: correct the `base_model` field in the model card metadata to the real, public parent.
- If you don't: identify the true parent (config architecture + weight shapes narrow it fast) and re-scan with that lineage in mind.
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 | gemma |
| license | mit |
| serialization | no safetensors pickle custom code |
| chat template | present (chat_template.jinja) · sha256:7de1c58e208eda46 |
| claimed lineage | google/gemma-3-270m-it |
| lineage verified | unverified — weights battery pending |
Full measured fingerprint
| library | coremltools |
| pipeline | text-generation |
| repo files | 16 — pickle: gemma3_monolithic_full_lut6.mlmodelc/analytics/coremldata.bin, gemma3_monolithic_full_lut6.mlmodelc/coremldata.bin, gemma3_monolithic_full_lut6.mlmodelc/weights/weight.bin |
| revision | 29616b4cd2f5 |
| HF snapshot | 14 downloads · 1 likes · updated 2026-02-15 · 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 22:29 | — | 0 |
Verdict badge
Ship the verdict in your README — it always shows the latest published analysis:
[](https://ingot.tools/models/anemll/anemll-gemma-3-270m-it-MONO-ctx512-lut6)