sbert_punc_case_ru

This capability utilizes a fine-tuned BERT model specifically designed for token classification tasks in the Russian language. It employs a transformer architecture that processes input text in a sequence, allowing for contextual understanding of each token based on its surrounding context. The model is trained on a large corpus of Russian text, enabling it to accurately classify tokens into predefined categories, which is essential for applications like named entity recognition and part-of-speech tagging.