sallani/EUAIAct-Qwen2.5-0.5B-Edge
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<img src="https://img.shields.io/badge/EU%20AI%20Act-Specialist-003189?style=for-the-badge&logoColor=white" /> <img src="https://img.shields.io/badge/Edge%20%7C%20Mobile%20%7C%20WebGPU-Offline%20Ready-111827?style=for-the-badge&logoColor=white" /> <img src="https://img.shields.io/badge/494M%20Parameters-SLM-f97316?style=for-the-badge&logoColor=white" /> <img src="https://img.shields.io/badge/License-Apache%202.0-22c55e?style=for-the-badge" />
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EUAIAct-Qwen2.5-0.5B-Edge
A compact, offline-first Language Model specialized in EU AI Act & GDPR
Runs on mobile browsers · laptops · edge servers — no cloud, no API, no data transfer
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Overview
EUAIAct-Qwen2.5-0.5B-Edge is a 494M parameter Small Language Model fine-tuned on the EU AI Act (Regulation EU 2024/1689) and GDPR compliance corpus.
It is designed to run entirely on-device — in a mobile browser via WebGPU, on Apple Silicon via MLX, or on any machine via GGUF. No internet connection required after download.
Advisory use only — not a substitute for qualified legal counsel.
✦ Key Features
- Offline-first — works without internet once downloaded
- Cross-platform — Windows · macOS · Linux · Mobile · Browser
- Mobile-ready — runs in browser via Transformers.js + WebGPU
- Multilingual — French 🇫🇷 and English 🇬🇧
- Lightweight — 350 MB (GGUF) to 1 GB (MLX full precision)
- Open weights — Apache 2.0, fully auditable
Deployment formats
Quickstart
🌐 Browser & Mobile — Transformers.js + WebGPU
import { pipeline } from '@xenova/transformers';
const ai = await pipeline(
'text-generation',
'sallani/EUAIAct-Qwen2.5-0.5B-Edge',
{ device: 'webgpu' }
);
const response = await ai(
"What are the obligations for high-risk AI system providers under Article 16?",
{ max_new_tokens: 400 }
);
console.log(response[0].generated_text);🍎 Apple Silicon — MLX
from mlx_lm import load, generate
model, tokenizer = load("sallani/EUAIAct-Qwen2.5-0.5B-Edge")
messages = [
{"role": "system", "content": "Tu es un expert EU AI Act et RGPD."},
{"role": "user", "content": "Qu'est-ce qu'un système IA à haut risque selon l'Article 6 ?"}
]
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
print(generate(model, tokenizer, prompt=prompt, max_tokens=512))🖥️ llama.cpp — Windows · macOS · Linux
llama-cli \
-m euaiact-qwen2.5-0.5b-q4_k_m.gguf \
--chat-template qwen \
-p "Explain the EU AI Act conformity assessment procedure." \
-n 512Model details
Training corpus
Covers the full regulatory stack for AI compliance in the EU:
Performance
Intended use
Target users: CISOs, DPOs, GRC consultants, legal counsel, compliance officers.
EU AI Act self-assessment
This model itself falls under limited risk (Article 50 — conversational AI system):
- Disclosure obligation: users must be informed they are interacting with AI
- No autonomous decisions — advisory only
- No personal data processed — on-device inference only
- Below GPAI threshold (< 10²³ training FLOPs)
Citation
@misc{allani2026euaiactedge,
author = {Allani, Sabri},
title = {EUAIAct-Qwen2.5-0.5B-Edge: A Sovereign Edge SLM for EU AI Act and GDPR Compliance},
year = {2026},
url = {https://huggingface.co/sallani/EUAIAct-Qwen2.5-0.5B-Edge},
note = {LoRA fine-tune of Qwen2.5-0.5B-Instruct on EU AI Act and GDPR corpus. Apache 2.0.}
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EU AI Act · GDPR · Edge · Mobile · Offline · Open Weights
Apache 2.0 — Free to use, modify, and distribute
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