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tiny random albert EU AI Act Compliance Profile

optimum-intel-internal-testing

① Risk Classification
MINIMAL
Voluntary
Minimal Risk AI System
② Model Info
CreatedOct 2025
SyncedApr 3, 2026
③ Popularity
69.1Kdownloads
0 likes
View on HuggingFace ↗
④ Obligations
1apply
~8h effort
□ AI Literacy (Art. 4)
$ npx complior scan

Your risk depends on how you use tiny random albert

Usage ContextRisk LevelObligations
Internal coding toolMINIMAL3 obligations (~12h)
Customer support botLIMITED7 obligations (~32h)
HR screening / hiringHIGH19 obligations (~120h)
Credit decisionsHIGH19 obligations (~120h)
Medical triageHIGH19 obligations (~120h)

Why this tool is classified as MINIMAL

tiny random albert is an AI model by optimum-intel-internal-testing. 69.1K downloads on HuggingFace.

Applicable Articles

Art. 4AI Literacy (Art. 4)
REQUIREDDEADLINE PASSED
›
Obligation under Art. 4 for tiny random albert deployers.

Who does what

optimum-intel-internal-testing (provider)Their job

  • Provider obligations being compiled

You (deployer)Your job

  • •AI Literacy (Art. 4) (Art. 4)
See full obligation checklist →

Risk Assessment Reasoning

This model is classified as Minimal Risk under the EU AI Act. No mandatory compliance obligations apply, but voluntary codes of practice are encouraged. AI literacy training (Art. 4) is recommended for all deployers.

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Frequently Asked Questions

What is tiny random albert's EU AI Act risk classification?

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tiny random albert is classified as MINIMAL under the EU AI Act.

What are my obligations if I deploy tiny random albert?

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As a tiny random albert deployer, you have 1 base obligations (~8 hours estimated effort). Key articles: Art. 4.

What is tiny random albert?

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tiny random albert is a Unknown model by optimum-intel-internal-testing. It has 69.1K downloads on HuggingFace.

What are the EU AI Act deadlines for tiny random albert?

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Already passed: AI Literacy (Art. 4) — 2025-02-02.

Check tiny random albert compliance in your codebase

One command to scan. Open-source CLI.

$ npx complior scan