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.
Runs of eolang Swahili-NER-BertBase-Cased on huggingface.co
9
Total runs
0
24-hour runs
-4
3-day runs
-3
7-day runs
0
30-day runs
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