How to use this model directly from the
tokenizer = AutoTokenizer.from_pretrained("DeepPavlov/rubert-base-cased-conversational") model = AutoModelWithLMHead.from_pretrained("DeepPavlov/rubert-base-cased-conversational")
Conversational RuBERT (Russian, cased, 12‑layer, 768‑hidden, 12‑heads, 180M parameters) was trained on OpenSubtitles, Dirty, Pikabu, and a Social Media segment of Taiga corpus. We assembled a new vocabulary for Conversational RuBERT model on this data and initialized the model with RuBERT.
: P. Lison and J. Tiedemann, 2016, OpenSubtitles2016: Extracting Large Parallel Corpora from Movie and TV Subtitles. In Proceedings of the 10th International Conference on Language Resources and Evaluation (LREC 2016)
: Shavrina T., Shapovalova O. (2017) TO THE METHODOLOGY OF CORPUS CONSTRUCTION FOR MACHINE LEARNING: «TAIGA» SYNTAX TREE CORPUS AND PARSER. in proc. of “CORPORA2017”, international conference , Saint-Petersbourg, 2017.