Pretrained models for recognising sex education concepts SemSEX 1.0
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.