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Tf Xlm Roberta Base

Developed by jplu
XLM-RoBERTa is an extended version of a cross-lingual sentence encoder, trained on 2.5T of data across 100 languages, achieving excellent performance in multiple cross-lingual benchmarks.
Downloads 4,820
Release Time : 3/2/2022

Model Overview

XLM-RoBERTa model for Tensorflow, supporting cross-lingual understanding tasks.

Model Features

Cross-lingual capability
Trained on data from 100 languages, it possesses strong cross-lingual understanding abilities.
Large-scale pre-training
Trained with 2.5T of data, the model has rich linguistic knowledge.
Tensorflow support
A model version specifically optimized for the Tensorflow framework.

Model Capabilities

Cross-lingual text understanding
Text encoding
Multilingual task processing

Use Cases

Natural Language Processing
Cross-lingual text classification
Performing classification tasks on texts in multiple languages.
Achieved state-of-the-art results in multiple cross-lingual benchmarks
Multilingual QA system
Building a QA system that supports multiple languages.
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