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xlm-roberta-flash-implementation
jinaai/xlm-roberta-flash-implementation
xlm-roberta-flash-implementation is a machine learning model from jinaai. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as cc-by-nc-4.0.
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.py183 KB · 98%
At a glance
- Library
- transformers
- License
- cc-by-nc-4.0
- Access
- Public
- Created
- Apr 9, 2024
- Updated
- Aug 20, 2026
- SHA
- bd55a5ec
Model card
From the Hugging Face model README
Core implementation of Jina XLM-RoBERTa
This implementation is adapted from XLM-Roberta. In contrast to the original implementation, this model uses Rotary positional encodings and supports flash-attention 2.
Models that use this implementation
Converting weights
Weights from an original XLMRoberta model can be converted using the convert_roberta_weights_to_flash.py script in the model repository.
- Library
- transformers
- License
- cc-by-nc-4.0
- Languages
- multilingual, af, am, ar, as, az
- Created
- Apr 9, 2024
- Updated
- Aug 20, 2026