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- language: multilingual
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  license: apache-2.0
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  datasets:
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  - wikipedia
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  ## Model Description
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- This model is a distilled version of the [BERT base multilingual model](bert-base-multilingual-cased). The code for the distillation process can be found
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- [here](https://github.com/huggingface/transformers/tree/master/examples/distillation). This model is cased: it does make a difference between english and English.
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  The model is trained on the concatenation of Wikipedia in 104 different languages listed [here](https://github.com/google-research/bert/blob/master/multilingual.md#list-of-languages).
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  The model has 6 layers, 768 dimension and 12 heads, totalizing 134M parameters (compared to 177M parameters for mBERT-base).
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+ language:
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+ - multilingual
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+ - af
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+ - sq
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+ - ar
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+ - an
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+ - hy
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+ - ast
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+ - az
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+ - ba
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+ - eu
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+ - bar
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+ - be
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+ - bn
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+ - inc
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+ - bs
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+ - br
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+ - bg
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+ - my
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+ - ca
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+ - ceb
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+ - ce
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+ - zh
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+ - cv
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+ - hr
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+ - cs
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+ - da
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+ - nl
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+ - en
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+ - et
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+ - fi
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+ - fr
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+ - gl
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+ - ka
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+ - de
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+ - el
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+ - gu
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+ - ht
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+ - he
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+ - hi
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+ - hu
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+ - is
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+ - io
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+ - id
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+ - ga
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+ - it
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+ - ja
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+ - jv
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+ - kn
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+ - kk
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+ - ky
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+ - ko
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+ - la
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+ - lv
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+ - lt
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+ - roa
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+ - nds
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+ - lm
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+ - mk
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+ - mg
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+ - ms
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+ - ml
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+ - mr
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+ - mn
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+ - min
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+ - ne
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+ - new
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+ - nb
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+ - nn
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+ - oc
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+ - fa
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+ - pms
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+ - pl
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+ - pt
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+ - pa
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+ - ro
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+ - ru
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+ - sco
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+ - sr
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+ - hr
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+ - scn
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+ - sk
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+ - sl
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+ - aze
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+ - es
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+ - su
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+ - sw
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+ - sv
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+ - tl
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+ - tg
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+ - th
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+ - ta
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+ - tt
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+ - te
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+ - tr
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+ - uk
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+ - ud
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+ - uz
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+ - vi
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+ - vo
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+ - war
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+ - cy
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+ - fry
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+ - pnb
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+ - yo
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  license: apache-2.0
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  datasets:
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  - wikipedia
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  ## Model Description
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+ This model is a distilled version of the [BERT base multilingual model](https://huggingface.co/bert-base-multilingual-cased/). The code for the distillation process can be found [here](https://github.com/huggingface/transformers/tree/main/examples/research_projects/distillation). This model is cased: it does make a difference between english and English.
 
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  The model is trained on the concatenation of Wikipedia in 104 different languages listed [here](https://github.com/google-research/bert/blob/master/multilingual.md#list-of-languages).
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  The model has 6 layers, 768 dimension and 12 heads, totalizing 134M parameters (compared to 177M parameters for mBERT-base).