# Text representation

XLM-RoBERTa is a large-scale cross-lingual sentence encoder, trained on 2.5TB of data across 100 languages, achieving excellent performance in multiple cross-lingual benchmarks.

A customized distilled version of distilbert-base-multilingual-cased, specifically optimized for Spanish language processing

This is a lightweight version of distilbert-base-multilingual-cased, supporting processing in three languages: English, Spanish, and Chinese, while maintaining the same representation accuracy as the original model.

This is a Ukrainian-specific version of the distilbert-base-multilingual-cased model, retaining the original model's representational capabilities and accuracy.