readme: ---
  license: cc-by-4.0
  widget:
  - text: This house was let out in tiny tenements and was inhabited by working people of all kinds--tailors, locksmiths, cooks, Germans ofsorts, girls picking up a living as best they could, petty clerks, etc.
    example_title: "Crime and Punishment"
  - text: Quixote having got on his back and the duke mounted a fine horse, they placed the duchess in the middle and set out for the castle.
    example_title: "Don Quixote"
  - text: The noble carriage of this gentleman, for whom he believed himself to be engaged, had won Planchet—that was the name of the Picard.
    example_title: "The Three Musketeers"
  ---
  ### Description
  A `roberta-base` model which has been fine tuned for token classification on the [LitBank](https://github.com/dbamman/litbank) dataset.
  
  ### Intended Use
  This model is ready to be used for entity recognition. It is capable of tagging the 6 entity types from [ACE 2005](https://www.ldc.upenn.edu/sites/www.ldc.upenn.edu/files/english-entities-guidelines-v6.6.pdf)
  - Person (PER)
  - ORG
  - GPE
  - LOC
  - VEH
  - FAC
  
  Due to the fine-tuning domain, it is expected to work best with literary sentences.
  