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rubert-base-cased-sentence
DeepPavlov/rubert-base-cased-sentence
rubert-base-cased-sentence is a feature extraction model from DeepPavlov. Use it when you need embeddings to search or compare text. It is set up for transformers.
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\[1\] google-translated t…
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At a glance
- Task
- Feature Extraction
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Mar 2, 2022
- Updated
- May 18, 2021
- SHA
- 78b5122d
Model card
From the Hugging Face model README
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[1] google-translated to russian and on russian part of XNLI dev set[2]. Sentence representations are mean pooled token embeddings in the same manner as in Sentence‑BERT[3].
[1]: 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
[2]: Williams A., Bowman S. (2018) XNLI: Evaluating Cross-lingual Sentence Representations. arXiv preprint arXiv:1809.05053
[3]: N. Reimers, I. Gurevych (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. arXiv preprint arXiv:1908.10084
- Task
- Feature Extraction
- Library
- transformers
- Type
- bert
- Languages
- ru
- Hf Inference
- live
- Created
- Mar 2, 2022
- Updated
- May 18, 2021