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---
tags:
- transformers
- xlm-roberta
library_name: transformers
license: cc-by-nc-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
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- km
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- ko
- ku
- ky
- la
- lo
- lt
- lv
- mg
- mk
- ml
- mn
- mr
- ms
- my
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- nl
- 'no'
- om
- or
- pa
- pl
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- pt
- ro
- ru
- sa
- sd
- si
- sk
- sl
- so
- sq
- sr
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- sw
- ta
- te
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- tl
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- ug
- uk
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- vi
- xh
- yi
- zh
---
Core implementation of Jina XLM-RoBERTa
This implementation is adapted from [XLM-Roberta](https://huggingface.co/docs/transformers/en/model_doc/xlm-roberta). In contrast to the original implementation, this model uses Rotary positional encodings and supports flash-attention 2.
### Models that use this implementation
- [jinaai/jina-embeddings-v3](https://huggingface.co/jinaai/jina-embeddings-v3)
- [jinaai/jina-colbert-v2](https://huggingface.co/jinaai/jina-colbert-v2)
### Converting weights
Weights from an [original XLMRoberta model](https://huggingface.co/FacebookAI/xlm-roberta-large) can be converted using the `convert_roberta_weights_to_flash.py` script in the model repository.
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