Swahili-NER-BertBase-Cased

Intended uses & limitations

How to use

You can use this model with Transformers pipeline for NER.

from transformers import pipeline
from transformers import AutoTokenizer, AutoModelForTokenClassification

tokenizer = AutoTokenizer.from_pretrained("eolang/Swahili-NER-BertBase-Cased")
model = AutoModelForTokenClassification.from_pretrained("eolang/Swahili-NER-BertBase-Cased")

nlp = pipeline("ner", model=model, tokenizer=tokenizer)
example = "Kwa nini Kenya inageukia mazao ya GMO kukabiliana na ukame"

ner_results = nlp(example)
print(ner_results)

Training data

This model was fine-tuned on the Swahili Version of the WikiAnn dataset for cross-lingual name tagging and linking based on Wikipedia articles in 295 languages

Training procedure

This model was trained on a single NVIDIA A 5000 GPU with recommended hyperparameters from the original BERT paper which trained & evaluated the model on CoNLL-2003 NER task.