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RuBERT-MultiCoNER

This is a BERT-based named entity recognizer for extracting named entities in Russian texts. Entities of the following six classes can be recognized:

  1. Persons, i.e. names of people (PER)
  2. Locations or physical facilities (LOC)
  3. Corporations and businesses (CORP)
  4. All other groups (GRP)
  5. Consumer products (PROD)
  6. Titles of creative works like movie, song, and book titles (CW).
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Model size
177M params
Tensor type
F32
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Dataset used to train bond005/rubert-multiconer