Model page

allenai/OLMo-2-0325-32B-SFT warn

Weights only ship in a format that can run code when loaded. Plus 1 minor note.

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 battery2026-08-25Behavioral batterynot rundetails
BatteryLooks atStatus
Static batteryMetadata & packagingcomplete 2026-08-25
Weights batteryWeights forensics — no GPU, no downloadcomplete 2026-08-25100,352-token embedding scanned · 413 undertrained · lineage consistent · pickle audit clean
Behavioral batteryLive-inference differentialsnot 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 (pytorch_model-00001-of-00014.bin, pytorch_model-00002-of-00014.bin, pytorch_model-00003-of-00014.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.

  1. Do not load the pickle files in-process — pickle deserialization executes arbitrary code from the file.
  2. 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.
  3. Pin the exact revision hash you converted from, and load only your converted safetensors artifact from then on.

low Undertrained tokens in vocabulary (non-ASCII tail)

Embedding-norm scan flagged 413 undertrained tokens (norm < 0.3× the vocabulary median), but 0 decode to plain-ASCII strings, so exposure in English-language pipelines is limited. 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.

  1. 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.
  2. 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.
  3. 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.

info Pickle static analysis clean

Opcode-level parse of pytorch_model-00001-of-00014.bin, pytorch_model-00002-of-00014.bin, pytorch_model-00003-of-00014.bin, pytorch_model-00004-of-00014.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.

info Weights consistent with claimed parent allenai/OLMo-2-0325-32B

Mean cosine similarity of 64 sampled token-embedding rows against allenai/OLMo-2-0325-32B is 1.000 — the weights plausibly descend from the declared base (relation: unspecified).

How to fix

Fix or verify the `base_model` declaration so lineage checks can run.

  1. If you own the repo: correct the `base_model` field in the model card metadata to the real, public parent.
  2. 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.

architectureolmo2 · 64 layers · 5120-dim
vocabulary100,352 tokens
licenseapache-2.0
serializationno safetensors pickle
chat templatepresent · sha256:ac7498a36a719da6
claimed lineageallenai/OLMo-2-0325-32B
lineage verifiedconsistent vs allenai/OLMo-2-0325-32B — embedding-row cosine 1.000
glitch-token surface413 undertrained candidates, 0 plain-ASCII
Full measured fingerprint
architecturesOlmo2ForCausalLM
librarytransformers
pipelinetext-generation
repo files24 — pickle: pytorch_model-00001-of-00014.bin, pytorch_model-00002-of-00014.bin, pytorch_model-00003-of-00014.bin, pytorch_model-00004-of-00014.bin, pytorch_model-00005-of-00014.bin, pytorch_model-00006-of-00014.bin, pytorch_model-00007-of-00014.bin, pytorch_model-00008-of-00014.bin, pytorch_model-00009-of-00014.bin, pytorch_model-00010-of-00014.bin
revisionce177b3fadb4
HF snapshot306 downloads · 4 likes · updated 2025-03-14 · captured 2026-08-25
pickle auditpytorch_model-00001-of-00014.bin, pytorch_model-00002-of-00014.bin, pytorch_model-00003-of-00014.bin, pytorch_model-00004-of-00014.bin3 standard global(s)
embedding tensormodel.embed_tokens.weight · BF16 · 100,352×5120
embedding normsmedian 66.256 · mean 62.9664
lineage checkconsistent — cosine 1 over 64 sampled rows vs allenai/OLMo-2-0325-32B
Battery runs (1)the run trace behind the findings — what each job measured
batterystatusqueueddurationattempts
weightscomplete2026-08-25 21:494m1
weights run 2026-08-25 measurements
probes runglitch-norm-scan, zero-template-token-scan, pickle-static-analysis, lineage-norm-correlation
probes skippedtoken-decode: no tokenizer.json
embedding tensormodel.embed_tokens.weight · BF16 · 100,352×5120
glitch surface413 undertrained, 0 plain-ASCII
lineage checkconsistent — cosine 1 over 64 rows vs allenai/OLMo-2-0325-32B

Verdict badge

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Ingot verdict: warn

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