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• Pretrained models for recognising sex education concepts SemSEX 1.0

  6 resources

  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.

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• Slovenian commonsense reasoning model SloMET-ATOMIC 2020

  2 resources

  The SloMET-ATOMIC 2020 is a Slovene commonsense reasoning model that is able to predict commonsense descriptions in a natural language for a given input sentence. The model is an adaptation of the Slovene GPT-2 model (https://huggingface.co/cjvt/gpt-sl-base) that has been finetuned using the SloATOMIC 2020 corpus (http://hdl.handle.net/11356/1724), consisting of 1.33M everyday interence knowledge tuples about entities and events. The released model is a pytorch neural network model, intended for usage with the transformers library (https://github.com/huggingface/transformers).

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