---
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.