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# Prefix optimization
Rubert Mini Uncased
MIT
This model is used to compute embedding vectors for Russian and English sentences, obtained by distilling the embedding vectors from ai-forever/FRIDA. The model is of the uncased type, meaning it does not distinguish between uppercase and lowercase letters in the text.
Text Embedding
Transformers Supports Multiple Languages
Transformers Supports Multiple LanguagesR
sergeyzh
724
3
BERTA
MIT
BERTA is obtained by distilling the embedding vectors of the FRIDA model into LaBSE-ru-turbo, which is used to calculate the embedding vectors of Russian and English sentences and supports multiple prefix tasks.
Text Embedding Transformers Supports Multiple Languages
Transformers Supports Multiple LanguagesB
sergeyzh
7,089
12
Rubert Mini Frida
MIT
A lightweight and fast modified version of the FRIDA model for computing embedding vectors of Russian and English sentences
Text Embedding Transformers Supports Multiple Languages
Transformers Supports Multiple LanguagesR
sergeyzh
1,203
9
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