ai model report

Is prithivMLmods/Age-Classification-SigLIP2 safe to load?

CLEAN risk. 3 of 34 tracked dependencies carry advisories. Driven by No version-matched advisories and no malicious packages..

View on HuggingFace

// posture

fig. 01 — posture on eight axes, 100 is clean. Weakest: scanner trust at 55.

// the finding

0.0xyz score out of 10CLEAN

LOWShips both safetensors and 17 pickle-format file(s); a consumer passing use_safetensors=False takes the pickle path.

2 more findings on this model.

Author: prithivMLmods
Task: image-classification
Loader: transformers
License: apache-2.0
Downloads: 97,245
Remote code: not required

// dependencies

7 direct, 4 with findings, 28 reachable

Package	Evidence	Advisories	Worst
transformers	direct, runtime	23	none pinned
torch	direct, inferred	13	none pinned
numpy	direct, install	8	hidden
huggingface-hub	direct, install	0	hidden
safetensors	direct, install	0	hidden
tokenizers	direct, install	0	hidden
annotated-doc	direct, install	0	hidden
anyio	direct, install	0	hidden

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Risk computed 2026-09-22 at 18:58 UTC. Dependencies come from the model's requirements, its declared loader and the code it ships; advisories from NVD, GHSA and OSV.