Model page

bigcode/santacoder-ldf warn

Weights only ship in a format that can run code when loaded; loading it runs custom code from the repo.

downloads 126likes 2license mitarch gpt2updated 2023-08-17

chat template: not found · view on Hugging Face ↗

Scan coverageStatic battery2026-08-26Weights battery2026-08-26Behavioral batterynot rundetails
BatteryLooks atStatus
Static batteryMetadata & packagingcomplete 2026-08-26
Weights batteryWeights forensics — no GPU, no downloadcomplete 2026-08-2649,280-token embedding scanned · 0 undertrained · pickle audit clean
Behavioral batteryLive-inference differentialsnot run

Ingot runs three batteries against a model. What each one checks →

Findings

Scanned 2026-08-26 · published from a community scan.

medium Pickle-serialized weights, no safetensors

Weights ship only as pickle-based files (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.

  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.

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.

  1. Read every `.py` file in the repo before first load — this code runs in your process.
  2. 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.
  3. Prefer a version of the architecture already in `transformers` if one exists, which removes the remote-code requirement entirely.

info Embedding-norm glitch scan clean

No undertrained tokens found: every non-special token's embedding norm is above 0.3× the vocabulary median (0.775). 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 (no code executed) found only standard serialization globals (4 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 2026-08-26.

architecturegpt2 · 24 layers · 2048-dim
vocabulary49,280 tokens
licensemit
serializationno safetensors pickle custom code
chat templatenone
glitch-token surfaceclean no undertrained tokens
Full measured fingerprint
architecturesGPT2LMHeadCustomModel
librarytransformers
pipelinetext-generation
repo files9 — pickle: pytorch_model.bin
revision32d4a3ac1818
HF snapshot126 downloads · 2 likes · updated 2023-08-17 · captured 2026-08-25
pickle auditpytorch_model.bin4 standard global(s)
embedding tensortransformer.wte.weight · BF16 · 49,280×2048
embedding normsmedian 0.7747 · mean 0.7668
lineage checkno claimed base model
Battery runs (1)the run trace behind the findings — what each job measured
batterystatusqueueddurationattempts
weightscomplete2026-08-25 21:5237s1
weights run 2026-08-25 measurements
probes runglitch-norm-scan, zero-template-token-scan, pickle-static-analysis, lineage-norm-correlation
embedding tensortransformer.wte.weight · BF16 · 49,280×2048
glitch surface0 undertrained, 0 plain-ASCII
lineage checknot checked (no claimed base model)

Verdict badge

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Ingot verdict: warn

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