# Load model directly
from transformers import AutoTokenizer, AutoModelForTokenClassification
tokenizer = AutoTokenizer.from_pretrained("nates/LER-roberta")
model = AutoModelForTokenClassification.from_pretrained("nates/LER-roberta")Quick Links
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.
- Downloads last month
- 9
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="nates/LER-roberta")