Safetensors
mpixel
pixel
mae
vit
tokenization-free
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+ ---
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+ license: apache-2.0
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+ datasets:
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+ - HuggingFaceFW/fineweb
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+ - HuggingFaceFW/fineweb-2
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+ language:
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+ - en
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+ - uk
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+ - zh
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+ - hi
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+ - da
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+ - tr
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+ - fi
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+ - es
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+ - ko
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+ - ar
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+ - th
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+ - el
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+ - bn
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+ - vi
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+ - he
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+ - fa
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+ tags:
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+ - pixel
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+ - mae
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+ - vit
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+ - tokenization-free
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+ ---
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+
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+ # MPIXEL
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+
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+ MPIXEL, introduced in [Scaling Multilingual Pretraining of Pixel Language Models](https://arxiv.org/abs/2610.29681), is a family of multilingual pixel language models, which operate on visually rendered text. Our main models, `mpixel-base` (86M parameters) and `mpixel-large` (307M parameters), are pretrained on sixteen languages that span ten writing systems. MPIXEL uses adaptive rendering: it renders text as grapheme bigrams by default, Chinese, Japanese and Korean text one character per patch, and Arabic and Hebrew text word by word.
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+
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+ ## Basic usage
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+ To use our models, please first install our [`mpixel` package](https://github.com/ilkerkesen/mpixel). Here is an example of loading a pretrained model and encoding input text:
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+
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+ ```python
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+ from transformers import AutoModel
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+ import mpixel.models.auto_register # registers MPIXEL with the Auto classes
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+ from mpixel.processing import MPIXELProcessor
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+
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+ processor = MPIXELProcessor.from_pretrained("Team-PIXEL/mpixel-base")
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+ model = AutoModel.from_pretrained("Team-PIXEL/mpixel-base")
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+
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+ inputs = processor(["Hello world!", "The quick brown fox jumps over the lazy dog."])
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+ outputs = model(**inputs)
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+
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+ print(outputs.last_hidden_state.shape) # torch.Size([2, 513, 768])
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+ ```
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+
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+ For further information, please take a look at our repository: [https://github.com/ilkerkesen/mpixel](https://github.com/ilkerkesen/mpixel).
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+
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+ ## Citation
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+
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+ If you find MPIXEL beneficial for your research, please cite it,
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+
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+ ```
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+ @misc{kesen2026scalingmultilingualpretrainingpixel,
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+ title={Scaling Multilingual Pretraining of Pixel Language Models},
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+ author={Ilker Kesen and Jenny Kunz and Kasra Malihi and Desmond Elliott},
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+ year={2026},
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+ eprint={2610.29681},
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+ archivePrefix={arXiv},
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+ primaryClass={cs.CL},
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+ url={https://arxiv.org/abs/2610.29681},
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+ }
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+ ```