Binary toxicity classifier for Ukrainian
This is the fine-tuned on the downstream task "xlm-roberta-large" instance.
The evaluation metrics for binary toxicity classification are:
Precision: 0.9468 Recall: 0.9465 F1: 0.9465
The training and evaluation data will be clarified later.
How to use
from transformers import AutoTokenizer, AutoModelForSequenceClassification
# load tokenizer and model weights
tokenizer = AutoTokenizer.from_pretrained('dardem/xlm-roberta-large-uk-toxicity')
model = AutoModelForSequenceClassification.from_pretrained('dardem/xlm-roberta-large-uk-toxicity')
# prepare the input
batch = tokenizer.encode('Ти неймовірна!', return_tensors='pt')
# inference
model(batch)
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