Edit model card

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
19
Safetensors
Model size
177M params
Tensor type
F32
·
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Dataset used to train bond005/rubert-multiconer