Pretrained models for recognising sex education concepts SemSEX 1.0

  Avtorji

Knez, Timotej ; Prezelj, Tim and Žitnik, Slavko

  Identifikator vnosa

http://hdl.handle.net/11356/1894

 URL projekta

https://github.com/TimotejK/SemSex

 Datum objave

2023-11-11

 Vrsta

toolService

 Jezik(i)

Slovenian

 Opis

Pretrained language models for detecting and classifying the presence of sex education concepts in Slovene curriculum documents. The models are PyTorch neural network models, intended for usage with the HuggingFace transformers library (https://github.com/huggingface/transformers). The models are based on the Slovenian RoBERTa contextual embeddings model SloBERTa 2.0 (http://hdl.handle.net/11356/1397) and on the CroSloEngual BERT model (http://hdl.handle.net/11356/1330). The source code of the model and example usage is available in GitHub repository https://github.com/TimotejK/SemSex. The models and tokenizers can be loaded using the AutoModelForSequenceClassification.from_pretrained() and the AutoTokenizer.from_pretrained() functions from the transformers library. An example of such usage is available at https://github.com/TimotejK/SemSex/blob/main/Concept%20detection/Classifiers/full_pipeline.py. The corpus on which these models have been trained is available at http://hdl.handle.net/11356/1895.

 Izdajatelj

CLARIN.SI

 Zahvala

Jožef Stefan Institute CLARIN "CLARIN.SI"

 Ključne besede

language model education sex ed knowledge extraction natural language processing

 Zbirke

CLARIN.SI data & tools

Prikaži polni zapis vnosa