tiny random ArceeForCausalLM (HF) EU AI Act Compliance Profile
onnx-internal-testing
Your risk depends on how you use tiny random ArceeForCausalLM (HF)
| Usage Context | Risk Level | Obligations |
|---|---|---|
| Internal coding tool | MINIMAL | 3 obligations (~12h) |
| Customer support bot | LIMITED | 7 obligations (~32h) |
| HR screening / hiring | HIGH | 19 obligations (~120h) |
| Credit decisions | HIGH | 19 obligations (~120h) |
| Medical triage | HIGH | 19 obligations (~120h) |
Why this tool is classified as GPAI
tiny random ArceeForCausalLM (HF) is a text generation model by onnx-internal-testing. Built with transformers. 3.8K downloads on HuggingFace.
Applicable Articles
Who does what
onnx-internal-testing (provider)Their job
- Provider obligations being compiled
You (deployer)Your job
- •AI Literacy (Art. 4) (Art. 4)
- •AI Disclosure (Art. 50) (Art. 50)
- •Synthetic Content Labeling (Art. 50) (Art. 50)
Risk Assessment Reasoning
This model is classified as General-Purpose AI (GPAI) under the EU AI Act. GPAI providers must comply with transparency obligations (Art. 53), including technical documentation and copyright policy disclosure. Deployers must ensure AI literacy training (Art. 4) for all staff interacting with the system. Text generation models may produce synthetic content; deployers using this for public-facing applications must disclose AI-generated content (Art. 50).
Similar Models
Frequently Asked Questions
What is tiny random ArceeForCausalLM (HF)'s EU AI Act risk classification?
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tiny random ArceeForCausalLM (HF) is classified as GPAI under the EU AI Act. However, the risk level of your specific deployment depends on your use case: internal tools may be Minimal risk, while HR screening or credit decisions escalate to High Risk.
What are my obligations if I deploy tiny random ArceeForCausalLM (HF)?
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As a tiny random ArceeForCausalLM (HF) deployer, you have 3 base obligations (~16 hours estimated effort). Key articles: Art. 4, Art. 50.
What is tiny random ArceeForCausalLM (HF)?
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tiny random ArceeForCausalLM (HF) is a Text Generation model by onnx-internal-testing. It has 3.8K downloads on HuggingFace.
What are the EU AI Act deadlines for tiny random ArceeForCausalLM (HF)?
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Already passed: AI Literacy (Art. 4) — 2025-02-02. Already passed: AI Disclosure (Art. 50) — 2025-08-02. Already passed: Synthetic Content Labeling (Art. 50) — 2025-08-02.
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