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HPLT’s First Release of Data and Models

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F24%3A10492846" target="_blank" >RIV/00216208:11320/24:10492846 - isvavai.cz</a>

  • Result on the web

    <a href="https://aclanthology.org/2024.eamt-2.27/" target="_blank" >https://aclanthology.org/2024.eamt-2.27/</a>

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    HPLT’s First Release of Data and Models

  • Original language description

    The High Performance Language Technologies (HPLT) project is a 3-year EU-funded project that started in September 2022. It aims to deliver free, sustainable, and reusable datasets, models, and workflows at scale using high-performance computing. We describe the first results of the project. The data release includes monolingual data in 75 languages at 5.6T tokens and parallel data in 18 language pairs at 96M pairs, derived from 1.8 petabytes of web crawls. Building upon automated and transparent pipelines, the first machine translation (MT) models as well as large language models (LLMs) have been trained and released. Multiple data processing tools and pipelines have also been made public.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2024

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Proceedings of the 25th Annual Conference of the European Association for Machine Translation (Volume 2)

  • ISBN

    978-1-06-869071-6

  • ISSN

  • e-ISSN

  • Number of pages

    2

  • Pages from-to

    53-54

  • Publisher name

    European Association for Machine Translation (EAMT)

  • Place of publication

    Sheffield, UK

  • Event location

    Sheffield, UK

  • Event date

    Jun 24, 2024

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article