AraFusion — 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: vanillabpe-641m-51479

Path in repo
`checkpoints/0-34500-v1.ckpt`
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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 — 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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