Create README.md

README.md

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+---
+language: 
+- multilingual
+- ar 
+- bn 
+- de 
+- el 
+- en
+- es
+- fi
+- fr
+- hi
+- id 
+- it
+- ja
+- ko
+- nl
+- pl
+- pt
+- ru
+- sv
+- sw
+- te
+- th
+- tr
+- vi
+- zh
+thumbnail: https://github.com/studio-ousia/luke/raw/master/resources/luke_logo.png
+tags:
+  - luke
+  - named entity recognition
+  - relation classification
+  - question answering
+license: apache-2.0
+---
+
+## mLUKE
+
+**mLUKE** (multilingual LUKE) is a multilingual extension of LUKE.
+
+Please check the [official repository](https://github.com/studio-ousia/luke) for
+more details and updates.
+
+This is the mLUKE base model with 12 hidden layers, 768 hidden size. The total number
+of parameters in this model is 561M.
+The model was initialized with the weights of XLM-RoBERTa(large) and trained using December 2020 version of Wikipedia in 24 languages.
+
+This model is a lite-weight version of [studio-ousia/mluke-large](https://huggingface.co/studio-ousia/mluke-large), without Wikipedia entity embeddings but only with special entities such as `[MASK]`.
+
+### Citation
+
+If you find mLUKE useful for your work, please cite the following paper:
+
+```latex
+@inproceedings{ri-etal-2022-mluke,
+    title = "m{LUKE}: {T}he Power of Entity Representations in Multilingual Pretrained Language Models",
+    author = "Ri, Ryokan  and
+      Yamada, Ikuya  and
+      Tsuruoka, Yoshimasa",
+    booktitle = "Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
+    year = "2022",
+    url = "https://aclanthology.org/2022.acl-long.505",
+```