Safetensors
mpixel
pixel
mae
vit
tokenization-free
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  1. README.md +60 -0
  2. config.json +33 -0
  3. model.safetensors +3 -0
  4. preprocessor_config.json +5 -0
README.md ADDED
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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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+ - ko
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+ - ar
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+ - th
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+ - el
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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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+ # 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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+ This model is `mpixel-8l`, which is pretrained on eight languages: English, Hindi, Chinese, Ukrainian, Korean, Thai, Modern Greek and Standard Arabic.
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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-8s")
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+ model = AutoModel.from_pretrained("Team-PIXEL/mpixel-8s")
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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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+ ```
config.json ADDED
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+ {
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+ "architectures": [
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+ "MPIXELForPreTraining"
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+ ],
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+ "attention_probs_dropout_prob": 0.1,
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+ "decoder_hidden_size": 512,
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+ "decoder_intermediate_size": 2048,
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+ "decoder_num_attention_heads": 16,
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+ "decoder_num_hidden_layers": 8,
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+ "dtype": "float32",
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+ "head_init": "pytorch",
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.1,
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+ "hidden_size": 768,
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+ "initializer_range": 0.02,
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+ "intermediate_size": 3072,
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+ "layer_norm_eps": 1e-12,
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+ "mask_ratio": 0.25,
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+ "max_num_patches": 512,
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+ "model_type": "mpixel",
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+ "norm_pix_loss": true,
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+ "num_attention_heads": 12,
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+ "num_channels": 3,
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+ "num_hidden_layers": 12,
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+ "patch_embedding_init": null,
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+ "patch_size": 16,
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+ "pooler_add_layer_norm": true,
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+ "pooling_mode": "mean",
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+ "qkv_bias": true,
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+ "reference_compile": false,
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+ "rope_theta": 160000.0,
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+ "transformers_version": "4.57.3"
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+ }
model.safetensors ADDED
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preprocessor_config.json ADDED
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+ {
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+ "patch_size": 16,
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+ "max_num_patches": 512,
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+ "font_size": 12
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+ }