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sallani/
EUAIAct-Qwen2.5-0.5B-Edge

Name: EUAIAct-Qwen2.5-0.5B-Edge
Availability: InStock

Qwen/Qwen2.5-0.5B-Instruct

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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

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

Format	Size	Runtime	Best for
ONNX INT8	~400 MB	Transformers.js	Browser · Mobile · WebGPU — Windows · macOS · Linux
GGUF Q4_K_M	~350 MB	llama.cpp	Windows · macOS · Linux · Edge servers
MLX BF16	~1.0 GB	mlx_lm	Apple Silicon only (M1/M2/M3/M4)

Quickstart

🌐 Browser & Mobile — Transformers.js + WebGPU

javascript

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

python

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

bash

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 512

Model details

Property	Value
Base model	`Qwen/Qwen2.5-0.5B-Instruct` (Apache 2.0)
Fine-tuning method	LoRA — r=8, α=16, 8 layers
Training hardware	Apple M4 Max · MLX
Parameters	494M
Training data	300 curated Q&A pairs — EU AI Act · GDPR
Languages	French 🇫🇷 · English 🇬🇧
Context length	1 024 tokens
License	Apache 2.0

Training corpus

Covers the full regulatory stack for AI compliance in the EU:

Regulation	Coverage
🏛️ EU AI Act (2024/1689)	Articles 1–113, Annexes I–XIII, risk classification, provider & deployer obligations, GPAI, conformity assessment
🔒 GDPR	AI training data, DPIAs, data subject rights, lawful basis

Performance

Format	RAM	Speed (CPU)	Speed (Apple Silicon)
MLX BF16	~2 GB	—	~80 tok/s (M4 Max)
ONNX INT8	~1.2 GB	~20 tok/s	~60 tok/s (WebGPU)
GGUF Q4_K_M	~1 GB	~25 tok/s	~90 tok/s

Intended use

Use case
EU AI Act compliance Q&A	✅
GDPR guidance for AI systems	✅
AI risk classification assistance	✅
GRC documentation support	✅
Formal legal advice	❌
Autonomous compliance decisions	❌

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

bibtex

@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.}
}

EU AI Act · GDPR · Edge · Mobile · Offline · Open Weights

Apache 2.0 — Free to use, modify, and distribute