The resource constitues of a hierarchically-structured system of data types, which is intended to be suitable for describing the inputs and output annotation types of a wide range of natural language processing applications which operate within the UIMA Framework. It is being developed in conjunc...
This resource contains model weights for five Transformer-based models: RoBERTa, GPT-2, T5, BART and COMET(BART). These models were implemented using HuggingFace, and fine-tuned on the following four commonsense reasoning tasks: Argument Reasoning Comprehension Task (ARCT), AI2 Reasoning Challen...
HuggingFace (pytorch) pre-trained roBERTa model in Portuguese, with 6 layers and 12 attention-heads, totaling 68M parameters. Pre-training was done on 10 million Portuguese sentences and 10 million English sentences from the Oscar corpus. Please cite: Santos, Rodrigo, João Rodrigues, Antóni...
A GF resource grammar for Estonian, implementing the language-neutral API of the GF Resource Grammar Library as well as a morphological synthesizer.
This set of materials pertains to a study on the production of explicit pronouns, null pronouns, and repeated-NP anaphors, in European Portuguese. A spreadsheet containing data from 73 participants (young adults), namely, count data for instances of the different types of anaphor that occurred in...
Albertina PT-* is a foundation, large language model for the Portuguese language. It is an encoder of the BERT family, based on the neural architecture Transformer and developed over the DeBERTa model, and with most competitive performance for this language. It has different versions that were...
Albertina PT-BR base is a foundation, large language model for American Portuguese from Brazil. 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 of...
Albertina PT-* is a foundation, large language model for the Portuguese language. It is an encoder of the BERT family, based on the neural architecture Transformer and developed over the DeBERTa model, and with most competitive performance for this language. It has different versions that were...