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High Performance Language Technologiesbroad

HPLT · Horizon Europe grant · 2022-09-01–2025-12-31

EC contribution

€3,880,688

Total cost

€4,058,288

Beneficiaries

8
About the data

Source: CORDIS (official EU open data), Horizon Europe. Framework HORIZON · call HORIZON-CL4-2021-DATA-01 · scheme HORIZON-IA · topic HORIZON-CL4-2021-DATA-01-03. CORDIS record →

Objective

High Performance Language Technologies (HPLT) is a space combining petabytes of natural language data with large-scale model training. With trillions of words of text, the space will be the largest open text collection. Cleaning and privacy protecting services improve the quality and ethical properties of the text. Going beyond static repositories that require the user to individually analyze each data set, the project will rate data sets by how much they improve end-to-end language models and machine translation systems. Continuous integration of models and data will result in free downloadable high-quality models for all official European Union languages and beyond. The models will be reproducible with information and evaluation metrics shown in a publicly available dashboard. By focusing on training at scale, the project complements the inference-focused European Language Grid, which in turn will be used for model deployment. Datasets, models and information about them will be published in recognized FAIR data repositories, aggregation catalogues and marketplaces for easy discovery, access, replication, and exploitation.

Beneficiaries (8)

OrganisationCountryRoleEC contributionSME
UNIVERZITA KARLOVA CZ coordinator €641,812
UNIVERSITETET I OSLO NO participant €752,814
TURUN YLIOPISTO FI participant €689,000
HELSINGIN YLIOPISTO FI participant €594,625
CESNET ZAJMOVE SDRUZENI PRAVNICKYCH OSOB CZ participant €415,000
PROMPSIT LANGUAGE ENGINEERING, SL ES participant €414,400 Yes
SIGMA2 AS NO participant €373,036
THE UNIVERSITY OF EDINBURGH UK associatedPartner

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Defence Finance Monitor is an analytical and informational product. Grant data is official CORDIS; payment and subscription happen on DFM Analysis.