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).
Downloads last month
83
Safetensors
Model size
177M params
Tensor type
F32
·
Inference Providers NEW
This model is not currently available via any of the supported third-party Inference Providers, and the model is not deployed on the HF Inference API.

Dataset used to train bond005/rubert-multiconer