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--- |
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license: apache-2.0 |
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language: |
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- en |
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- ru |
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- es |
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- fr |
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- de |
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- it |
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- pt |
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- pl |
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- nl |
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- vi |
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- tr |
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- sv |
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- id |
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- ro |
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- cs |
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- zh |
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- hu |
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- ja |
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- th |
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- fi |
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- fa |
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- uk |
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- da |
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- el |
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- "no" |
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- bg |
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- sk |
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- ko |
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- ar |
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- lt |
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- ca |
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- sl |
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- he |
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- et |
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- lv |
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- hi |
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- sq |
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- ms |
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- az |
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- sr |
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- ta |
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- hr |
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- kk |
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- is |
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- ml |
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- mr |
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- te |
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- af |
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- gl |
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- fil |
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- be |
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- mk |
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- eu |
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- bn |
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- ka |
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- mn |
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- bs |
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- uz |
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- ur |
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- sw |
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- yue |
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- ne |
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- kn |
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- kaa |
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- gu |
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- si |
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- cy |
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- eo |
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- la |
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- hy |
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- ky |
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- tg |
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- ga |
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- mt |
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- my |
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- km |
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- tt |
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- so |
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- ku |
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- ps |
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- pa |
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- rw |
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- lo |
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- ha |
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- dv |
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- fy |
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- lb |
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- ckb |
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- mg |
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- gd |
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- am |
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- ug |
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- ht |
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- grc |
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- hmn |
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- sd |
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- jv |
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- mi |
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- tk |
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- ceb |
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- yi |
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- ba |
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- fo |
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- or |
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- xh |
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- su |
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- kl |
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- ny |
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- sm |
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- sn |
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- co |
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- zu |
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- ig |
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- yo |
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- pap |
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- st |
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- haw |
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- as |
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- oc |
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- cv |
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- lus |
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- tet |
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- gsw |
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- sah |
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- br |
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- rm |
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- sa |
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- bo |
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- om |
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- se |
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- ce |
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- cnh |
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- ilo |
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- hil |
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- udm |
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- os |
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- lg |
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- ti |
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- vec |
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- ts |
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- tyv |
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- kbd |
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- ee |
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- iba |
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- av |
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- kha |
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- to |
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- tn |
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- nso |
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- fj |
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- zza |
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- ak |
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- ada |
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- otq |
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- dz |
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- bua |
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- cfm |
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- ln |
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- chm |
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- gn |
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- krc |
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- wa |
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- hif |
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- yua |
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- srn |
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- war |
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- rom |
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- bik |
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- pam |
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- sg |
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- lu |
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- ady |
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- kbp |
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- syr |
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- ltg |
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- myv |
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- iso |
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- kac |
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- bho |
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- ay |
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- kum |
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- qu |
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- za |
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- pag |
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- ngu |
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- ve |
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- pck |
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- zap |
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- tyz |
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- hui |
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- bbc |
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- tzo |
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- tiv |
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- ksd |
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- gom |
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- min |
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- ang |
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- nhe |
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- bgp |
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- nzi |
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- nnb |
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- nv |
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- zxx |
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- bci |
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- kv |
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- new |
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- mps |
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- alt |
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- meu |
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- bew |
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- fon |
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- iu |
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- abt |
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- mgh |
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- mnw |
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- tvl |
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- dov |
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- tlh |
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- ho |
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- kw |
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- mrj |
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- meo |
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- crh |
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- mbt |
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- emp |
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- ace |
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- ium |
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- mam |
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- gym |
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- mai |
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- crs |
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- pon |
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- ubu |
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- fip |
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- quc |
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- gv |
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- kj |
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- btx |
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- ape |
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- chk |
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- rcf |
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- shn |
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- tzh |
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- mdf |
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- ppk |
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- ss |
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- gag |
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- cab |
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- kri |
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- seh |
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- ibb |
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- tbz |
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- bru |
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- enq |
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- ach |
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- cuk |
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- kmb |
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- wo |
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- kek |
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- qub |
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- tab |
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- bts |
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- kos |
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- rwo |
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- cak |
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- tuc |
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- bum |
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- cjk |
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- gil |
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- stq |
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- tsg |
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- quh |
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- mak |
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- arn |
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- ban |
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- jiv |
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- sja |
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- yap |
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- tcy |
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- toj |
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- twu |
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- xal |
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- amu |
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- rmc |
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- hus |
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- nia |
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- kjh |
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- bm |
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- guh |
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- mas |
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- acf |
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- dtp |
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- ksw |
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- bzj |
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- din |
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- zne |
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- mad |
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- msi |
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- mag |
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- mkn |
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- kg |
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- lhu |
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- ch |
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- qvi |
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- mh |
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- djk |
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- sus |
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- mfe |
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- srm |
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- dyu |
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- ctu |
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- gui |
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- pau |
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- inb |
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- bi |
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- mni |
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- guc |
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- jam |
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- wal |
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- jac |
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- bas |
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- gor |
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- skr |
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- nyu |
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- noa |
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- sda |
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- gub |
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- nog |
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- cni |
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- teo |
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- tdx |
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- sxn |
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- rki |
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- nr |
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- frp |
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- alz |
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- taj |
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- lrc |
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- cce |
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- rn |
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- jvn |
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- hvn |
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- nij |
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- dwr |
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- izz |
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- msm |
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- bus |
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- ktu |
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- chr |
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- maz |
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- tzj |
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- suz |
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- knj |
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- bim |
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- gvl |
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- bqc |
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- tca |
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- pis |
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- prk |
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- laj |
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- mel |
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- qxr |
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- niq |
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- ahk |
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- shp |
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- hne |
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- spp |
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- koi |
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- krj |
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- quf |
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- luz |
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- agr |
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- tsc |
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- mqy |
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- gof |
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- gbm |
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- miq |
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- dje |
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- awa |
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- bjj |
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- qvz |
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- sjp |
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- tll |
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- raj |
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- kjg |
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- bgz |
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- quy |
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- cbk |
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- akb |
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- oj |
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- ify |
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- mey |
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- ks |
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- cac |
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- brx |
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- qup |
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- syl |
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- jax |
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- ff |
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- ber |
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- tks |
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- trp |
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- mrw |
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- adh |
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- smt |
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- srr |
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- ffm |
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- qvc |
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- mtr |
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- ann |
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- kaa |
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- aa |
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- noe |
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- nut |
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- gyn |
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- kwi |
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- xmm |
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- msb |
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library_name: transformers |
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tags: |
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- text-generation-inference |
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datasets: |
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- allenai/MADLAD-400 |
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--- |
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This model has the safetensors weights for [Madlad-400](https://github.com/google-research/google-research/tree/master/madlad_400) 8B param language model. |
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There's currently no Python code to run inference. See details in this [thread](https://huggingface.co/jbochi/madlad400-3b-mt/discussions/2#6548f33cc6cd77f0a7c9798a) |
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Available language models models: |
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- [3B](https://huggingface.co/jbochi/madlad400-3b-mt) |
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- [7B](https://huggingface.co/jbochi/madlad400-7b-mt) |
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- [7B-BT](https://huggingface.co/jbochi/madlad400-7b-mt-bt) |
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- [10B](https://huggingface.co/jbochi/madlad400-10b-mt) |
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Article: [MADLAD-400: A Multilingual And Document-Level Large Audited Dataset](https://arxiv.org/abs/2309.04662) |
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Abstract: |
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> We introduce MADLAD-400, a manually audited, general domain 3T token monolingual dataset based on CommonCrawl, spanning 419 languages. We discuss the limitations revealed by self-auditing MADLAD-400, and the role data auditing had in the dataset creation process. We then train and release a 10.7B-parameter multilingual machine translation model on 250 billion tokens covering over 450 languages using publicly available data, and find that it is competitive with models that are significantly larger, and report the results on different domains. In addition, we train a 8B-parameter language model, and assess the results on few-shot translation. We make the baseline models available to the research community. |
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