How to use this model directly from the
tokenizer = AutoTokenizer.from_pretrained("DeepPavlov/rubert-base-cased-sentence") model = AutoModelWithLMHead.from_pretrained("DeepPavlov/rubert-base-cased-sentence")
Sentence RuBERT (Russian, cased, 12-layer, 768-hidden, 12-heads, 180M parameters) is a representation‑based sentence encoder for Russian. It is initialized with RuBERT and fine‑tuned on SNLI google-translated to russian and on russian part of XNLI dev set. Sentence representations are mean pooled token embeddings in the same manner as in Sentence‑BERT.
: S. R. Bowman, G. Angeli, C. Potts, and C. D. Manning. (2015) A large annotated corpus for learning natural language inference. arXiv preprint arXiv:1508.05326
: Williams A., Bowman S. (2018) XNLI: Evaluating Cross-lingual Sentence Representations. arXiv preprint arXiv:1809.05053
: N. Reimers, I. Gurevych (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. arXiv preprint arXiv:1908.10084