What are the hardware requirements for Ruqlm?

Ruqlm requires a context window of 0.5K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Ruqlm and how large is it?

Ruqlm is developed by Ruqiya. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

Ruqlm is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Name: Ruqlm
Author: Ruqiya

Ruqlm is an open-source language model by Ruqiya. Features: LLM, Context: 0.5K, License: apache-2.0, LLM Explorer Score: 0.33.

LLM Name	Ruqlm
Repository 🤗	https://huggingface.co/Ruqiya/ruqlm
Required VRAM	0 GB
Updated	2026-08-31
Maintainer	Ruqiya
Model Type	ruqlm
Model Files	0.0 GB 0.1 GB 0.0 GB 0.1 GB 0.0 GB
Supported Languages	ar
Model Architecture	RuqLM
License	apache-2.0
Context Length	512
Model Max Length	512
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	<pad>
Vocabulary Size	8192

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Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation