Averroes-Q-Instruct: A Bilingual Arabic-English 7B Instruction-Tuned Model for the Hayula Ecosystem

We present Averroes-Q-Instruct (ابن رشد), a bilingual Arabic-English 7-billion parameter instruction-tuned language model built on Qwen2.5-7B-Instruct. The model was fine-tuned on 55K human-written instructions spanning both Arabic and English, using Low-Rank Adaptation (LoRA) via the MLX framework on a single Apple M2 Ultra workstation with 192GB unified memory. Averroes-Q-Instruct achieves a final training loss of 1.434, demonstrating effective bilingual instruction following without catastrophic forgetting of the base model's capabilities. The model serves as the foundational base for the Saif (سيف) multi-expert cybersecurity AI suite, providing bilingual Arabic-English competence that enables specialized cybersecurity models to operate across both languages. Named after the Andalusian polymath Ibn Rushd (Averroes), the model embodies the principle of bridging intellectual traditions. We release Averroes-Q-Instruct under the Apache 2.0 license at BinSaqban/Averroes-Q-Instruct and hayulalab/Averroes-Q-Instruct on HuggingFace.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-07-24
DOI
https://doi.org/10.5281/zenodo.21537047
Primary Topic
Information and Cyber Security
Type
article
Field-Weighted Citation Impact
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article

Averroes-Q-Instruct: A Bilingual Arabic-English 7B Instruction-Tuned Model for the Hayula Ecosystem

Yahya Saqban
Zenodo (CERN European Organization for Nuclear Research)
Information and Cyber Security
article

Averroes-Q-Instruct: A Bilingual Arabic-English 7B Instruction-Tuned Model for the Hayula Ecosystem

Yahya Saqban
article en

Abstract

We present Averroes-Q-Instruct (ابن رشد), a bilingual Arabic-English 7-billion parameter instruction-tuned language model built on Qwen2.5-7B-Instruct. The model was fine-tuned on 55K human-written instructions spanning both Arabic and English, using Low-Rank Adaptation (LoRA) via the MLX framework on a single Apple M2 Ultra workstation with 192GB unified memory. Averroes-Q-Instruct achieves a final training loss of 1.434, demonstrating effective bilingual instruction following without catastrophic forgetting of the base model's capabilities. The model serves as the foundational base for the Saif (سيف) multi-expert cybersecurity AI suite, providing bilingual Arabic-English competence that enables specialized cybersecurity models to operate across both languages. Named after the Andalusian polymath Ibn Rushd (Averroes), the model embodies the principle of bridging intellectual traditions. We release Averroes-Q-Instruct under the Apache 2.0 license at BinSaqban/Averroes-Q-Instruct and hayulalab/Averroes-Q-Instruct on HuggingFace.

Zenodo (CERN European Organization for Nuclear Research)
Tula University (RU)
Quality Education
Openalex Percentile: Top 3%
Information and Cyber Security
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Averroes-Q-Instruct: A Bilingual Arabic-English 7B Instruction-Tuned Model for the Hayula Ecosystem — Yahya Saqban · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS