distilrubert-base-cased-conversational
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distilrubert-small-cased-conversational
DeepPavlov基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗distilrubert-tiny-cased-conversational
DeepPavlov基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗roberta-large-winogrande
DeepPavlov基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗rubert-base-cased
DeepPavlovRuBERT \(Russian, cased, 12‑layer, 768‑hidden, 12‑heads, 180M parameters\) was trained on the Russian part of Wikipedia and news data. We used this training data to build a vocabulary of Russian subtokens and took a multilingual version of BERT‑base as an initialization for RuBERT\[1\]. \[1\]: Kuratov, Y., Arkhipov, M. \(2019\). Adaptation of Deep Bidirectional Multilingual Transformers for Russian Language. arXiv preprint arXiv:1905.07213.
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View details ↗rubert-base-cased-conversational
DeepPavlov基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗rubert-base-cased-sentence
DeepPavlovSentence 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
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View details ↗rudialogpt3_medium_based_on_gpt2_v2
DeepPavlov基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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