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  • EdUKate Czech-Ukrainian translation model 2024

    This package includes Czech-to-Ukrainian translation model adapted for the educational domain. The model is exported into the TensorFlow Serving format (using Tensor2tensor version 1.6.6), so it can be used in the Charles Translator service (https://translator.cuni.cz) and in the web portal Škola s nadhledem. This model was developed within the EdUKate project, which aims to help mitigate language barriers between non-Czech-speaking children in the Czech Republic and the education in the Czech school system. The project focuses on the development and dissemination of multilingual digital learning materials for students in primary and secondary schools.

  • 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.