What are the hardware requirements for Aragpt2 Base?

Aragpt2 Base requires approximately 0.6 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Aragpt2 Base and how large is it?

Aragpt2 Base is developed by aubmindlab, a model with 1.5b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

Where can I download or evaluate Aragpt2 Base?

Aragpt2 Base is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Aragpt2 Base by aubmindlab — VRAM 0.6GB

Name: Aragpt2 Base
Author: aubmindlab

Aragpt2 Base is an open-source language model by aubmindlab. Features: 1.5b LLM, VRAM: 0.6GB, LLM Explorer Score: 0.02.

Arxiv:2012.15520 Ar Endpoints compatible Gpt2 Jax Pytorch Region:us Safetensors Tensorboard Tf

Model Card on HF 🤗: https://huggingface.co/aubmindlab/aragpt2-base

Aragpt2 Base Parameters and Internals

LLM Name	Aragpt2 Base
Repository 🤗	https://huggingface.co/aubmindlab/aragpt2-base
Model Size	1.5b
Required VRAM	0.6 GB
Updated	2026-07-28
Maintainer	aubmindlab
Model Type	gpt2
Model Files	0.6 GB 0.6 GB
Supported Languages	ar
Model Architecture	GPT2LMHeadModel
Vocabulary Size	64000
Activation Function	gelu_new

Rank the Aragpt2 Base capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

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

Best Alternatives to Aragpt2 Base

Best Alternatives	Context / RAM	Downloads	Likes
Via 1.5B Core	0K / 1.4 GB	42	1
LaMini GPT 1.5B	0K / 6.3 GB	248	39
Aragpt2 Medium	0K / 1.5 GB	851	11

Note: green Score (e.g. "73.2") means that the model is better than aubmindlab/aragpt2-base.