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 This is a very small distilled version of the [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) model for Russian and English.
 
-This model is useful if you want to fine-tune it for a relatively simple Russian task (e.g. NER or sentiment classification), and you care more about speed and size thanabout accuracy. It is approximately x10 faster than [DeepPavlov/rubert-base-cased-sentence](https://huggingface.co/DeepPavlov/rubert-base-ca (sed-sentence).
+This model is useful if you want to fine-tune it for a relatively simple Russian task (e.g. NER or sentiment classification), and you care more about speed and size than about accuracy. It is approximately x10 faster than [DeepPavlov/rubert-base-cased-sentence](https://huggingface.co/DeepPavlov/rubert-base-cased-sentence).
 
-It was trained on the [Yandex Translate corpus](https://translate.yandex.ru/corpus) using MLM loss (partially distilled from `bert-base-multilingual-cased`) and translation ranking loss (partially distilled from [LaBSE](https://huggingface.co/sentence-transformers/LaBSE)).
+It was trained on the [Yandex Translate corpus](https://translate.yandex.ru/corpus) using MLM loss (partially distilled from [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased)) and translation ranking loss (partially distilled from [LaBSE](https://huggingface.co/sentence-transformers/LaBSE)).