AraFusion โ Arabic Masked Diffusion Language Model
Trained with MDLM on FineWeb-2 Arabic subsets. Supports dialect-conditioned generation via Classifier-Free Guidance (CFG).
Model details
| Architecture | DiT (BERT-base scale: 12L / 12H / 768d) |
| Vocab | 96 000 (MorphBPE, see AraFusion/arafusion-morphBPE) |
| Sequence length | 512 tokens |
| Diffusion | Linear noise schedule, 1 000 sampling steps |
| Dialects | MSA ([MSA]), Najdi ([NAJDI]), Egyptian ([EGYPT]) |
| CFG p_uncond | 0.10 |
| Training steps | 200 000 (pre-train) |
| Precision | BF16 |
Data
Trained on three FineWeb-2 Arabic subsets:
| Subset | Dialect | Split |
|---|---|---|
arb_Arab |
Modern Standard Arabic | train 10 % |
ars_Arab |
Najdi / Saudi Arabic | train (full) |
arz_Arab |
Egyptian Arabic | train (full) |
See AraFusion/arafusion-arabic-raw for the raw text and
AraFusion/arafusion-arabic-packed for the packed training sequences.
Checkpoints
Training job: charlevel-641m-51502
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|---|
checkpoints/0-1000-v1.ckpt |
checkpoints/0-1000-v2.ckpt |
checkpoints/0-1000.ckpt |
checkpoints/0-100000.ckpt |
checkpoints/0-102000.ckpt |
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checkpoints/0-41500-v1.ckpt |
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checkpoints/0-50000-v1.ckpt |
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checkpoints/0-96000.ckpt |
checkpoints/0-98000.ckpt |
checkpoints/best.ckpt |
checkpoints/last-v1.ckpt |
checkpoints/last.ckpt |
Usage
# Requires the MDLM library from https://github.com/kuleshov-group/mdlm
from transformers import PreTrainedTokenizerFast
tok = PreTrainedTokenizerFast.from_pretrained("AraFusion/arafusion-morphBPE")
# Load checkpoint and run a sampling step โ see MDLM docs for full API.
Citation
@misc{arafusion2026,
title = {AraFusion: Dialect-Conditioned Arabic Masked Diffusion Language Model},
year = {2026},
url = {https://huggingface.co/AraFusion}
}
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