Model page

franco-rojas/bloom-560m-finetuned-tfmviu warn

Weights only ship in a format that can run code when loaded.

downloads 26likes 0license bigscience-bloom-rail-1.0arch bloomupdated 2023-09-30

claims base: bigscience/bloom-560m · chat template: not found · view on Hugging Face ↗

Scan coverageStatic battery2026-08-27Weights battery2026-08-27Behavioral batterynot rundetails
BatteryLooks atStatus
Static batteryMetadata & packagingcomplete 2026-08-27
Weights batteryWeights forensics: no GPU, no downloadcomplete 2026-08-27250,880-token embedding scanned · 0 undertrained · lineage consistent · pickle audit clean
Behavioral batteryLive-inference differentialsnot run

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

Findings

Scanned 2026-08-27 · published from a community scan.

medium Pickle-serialized weights, no safetensors

Weights ship only as pickle-based files (pytorch_model.bin, training_args.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.

info Embedding-norm glitch scan clean

No undertrained tokens found: every non-special token's embedding norm is above 0.3× the vocabulary median (0.387). 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 (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 bigscience/bloom-560m

Mean cosine similarity of 64 sampled token-embedding rows against bigscience/bloom-560m is 1.000 — the weights plausibly descend from the declared base (relation: unspecified).

Remediation guidance addresses the documented findings only. It is evidence-driven repair, not a safety certification of the model.

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Fingerprint

The durable profile of this model: measured weights-and-metadata facts, rebuilt on every scan and battery run. Updated 2026-08-27.

architecturebloom · 24 layers · 1024-dim
vocabulary250,880 tokens
licensebigscience-bloom-rail-1.0
serializationno safetensors pickle
chat templatenone
claimed lineagebigscience/bloom-560m
lineage verifiedconsistent vs bigscience/bloom-560m — embedding-row cosine 1.000
glitch-token surfaceclean no undertrained tokens
Full measured fingerprint
architecturesBloomForCausalLM
librarytransformers
pipelinetext-generation
repo files6 — pickle: pytorch_model.bin, training_args.bin
revision638990e90e8b
HF snapshot12 downloads · 0 likes · updated 2023-09-30 · captured 2026-08-25
pickle auditpytorch_model.bin — 3 standard global(s)
embedding tensortransformer.word_embeddings.weight · F32 · 250,880×1024
embedding normsmedian 0.3874 · mean 0.3643
lineage checkconsistent — cosine 1 over 64 sampled rows vs bigscience/bloom-560m
Battery runs (1)the run trace behind the findings — what each job measured
batterystatusqueueddurationattempts
weightscomplete2026-08-25 22:4189s1
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 tensortransformer.word_embeddings.weight · F32 · 250,880×1024
glitch surface0 undertrained, 0 plain-ASCII
lineage checkconsistent — cosine 1 over 64 rows vs bigscience/bloom-560m

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Ingot verdict: warn

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