Gervásio PT-PT base

Gervásio PT-* is a foundation, large language model for the Portuguese language. It is a decoder of the GPT family, based on the neural architecture Transformer and developed over the Pythia model, with competitive performance for this language. It has different versions that were trained for ...

Resource Type:Language Description
Media Type:Text
Language:Portuguese
Albertina PT-PT base

Albertina PT-PT base is a foundation, large language model for European Portuguese from Portugal. It is an encoder of the BERT family, based on the neural architecture Transformer and developed over the DeBERTa model, with most competitive performance for this language. It is distributed free ...

Resource Type:Language Description
Media Type:Text
Language:Portuguese
English-Danish Parallel corpus from Tatoeba project (Processed)

This dataset has been created within the framework of the European Language Resource Coordination (ELRC) Connecting Europe Facility - Automated Translation (CEF.AT) action. For further information on the project: http://lr-coordination.eu. Parallel corpus from English-Danish translations from ta...

Resource Type:Corpus
Media Type:Text
Languages:Danish
English
English-Norwegian parallel corpus from Forbruker Europa, 2017 release (Processed)

This dataset has been created within the framework of the European Language Resource Coordination (ELRC) Connecting Europe Facility - Automated Translation (CEF.AT) action. For further information on the project: http://lr-coordination.eu. Forbruker Europa is the Norwegian office of the European...

Resource Type:Corpus
Media Type:Text
Languages:Bokmål, Norwegian; Norwegian Bokmål
English
Corpus of Semantic Graphs with associated English strings

Automatically generated corpus of 98,818 graph/string pairs.

Resource Type:Corpus
Media Type:Text
Language:American English
Burst-Annotated Co-Occurrence Network for the Arab Spring Domain

A burst-annotated co-occurrence network about the Arab Spring topic built on the top of New York Times article snapshots from the years 2010-2013.

Resource Type:Corpus
Media Type:Text
Language:American English

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