### 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.

{"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\u2014that was the name of the Picard.", "example_title": "The Three Musketeers"}]}
transformers pytorch roberta token-classification license:cc-by-4.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #roberta #token-classification #license-cc-by-4.0 #autotrain_compatible #endpoints_compatible #region-us 

### Description
A 'roberta-base' model which has been fine tuned for token classification on the 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
- Person (PER)
- ORG
- GPE
- LOC
- VEH
- FAC

Due to the fine-tuning domain, it is expected to work best with literary sentences.

### Description
A 'roberta-base' model which has been fine tuned for token classification on the 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
- Person (PER)
- ORG
- GPE
- LOC
- VEH
- FAC

Due to the fine-tuning domain, it is expected to work best with literary sentences.
TAGS
#transformers #pytorch #roberta #token-classification #license-cc-by-4.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### Description
A 'roberta-base' model which has been fine tuned for token classification on the 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
- Person (PER)
- ORG
- GPE
- LOC
- VEH
- FAC

Due to the fine-tuning domain, it is expected to work best with literary sentences.
passage: TAGS
#transformers #pytorch #roberta #token-classification #license-cc-by-4.0 #autotrain_compatible #endpoints_compatible #region-us 
### Description
A 'roberta-base' model which has been fine tuned for token classification on the 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
- Person (PER)
- ORG
- GPE
- LOC
- VEH
- FAC

Due to the fine-tuning domain, it is expected to work best with literary sentences.