|
--- |
|
license: cc-by-4.0 |
|
language: |
|
- multilingual |
|
- af |
|
- am |
|
- ar |
|
- as |
|
- az |
|
- be |
|
- bg |
|
- bn |
|
- br |
|
- bs |
|
- ca |
|
- cs |
|
- cy |
|
- da |
|
- de |
|
- el |
|
- en |
|
- eo |
|
- es |
|
- et |
|
- eu |
|
- fa |
|
- fi |
|
- fr |
|
- fy |
|
- ga |
|
- gd |
|
- gl |
|
- gu |
|
- ha |
|
- he |
|
- hi |
|
- hr |
|
- hu |
|
- hy |
|
- id |
|
- is |
|
- it |
|
- ja |
|
- jv |
|
- ka |
|
- kk |
|
- km |
|
- kn |
|
- ko |
|
- ku |
|
- ky |
|
- la |
|
- lo |
|
- lt |
|
- lv |
|
- mg |
|
- mk |
|
- ml |
|
- mn |
|
- mr |
|
- ms |
|
- my |
|
- ne |
|
- nl |
|
- no |
|
- om |
|
- or |
|
- pa |
|
- pl |
|
- ps |
|
- pt |
|
- ro |
|
- ru |
|
- sa |
|
- sd |
|
- si |
|
- sk |
|
- sl |
|
- so |
|
- sq |
|
- sr |
|
- su |
|
- sv |
|
- sw |
|
- ta |
|
- te |
|
- th |
|
- tl |
|
- tr |
|
- ug |
|
- uk |
|
- ur |
|
- uz |
|
- vi |
|
- xh |
|
- yi |
|
- zh |
|
- an |
|
- ast |
|
- ba |
|
- bar |
|
- inc |
|
- ceb |
|
- ce |
|
- cv |
|
- ht |
|
- io |
|
- roa |
|
- nds |
|
- lm |
|
- min |
|
- new |
|
- nb |
|
- nn |
|
- oc |
|
- pms |
|
- sco |
|
- scn |
|
- aze |
|
- tg |
|
- tt |
|
- ud |
|
- vo |
|
- war |
|
- fry |
|
- pnb |
|
- yo |
|
tags: |
|
- multilingual |
|
- bert |
|
- roberta |
|
- xlmr |
|
- bm |
|
--- |
|
## Model type: Transformer-based masked language model |
|
## Training data: No additional pretraining, merges two existing models |
|
## Languages: 100+ languages |
|
# Architecture: |
|
- Base architectures: |
|
- XLM-RoBERTa base (multilingual) |
|
- BERT base cased (multilingual) |
|
|
|
## Custom merging technique to combine weights from both base models into one unified model |
|
|
|
# Mask token: <mask> |