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s-nlp / roberta_first_toxicity_classifier
Model's Last Updated: November 08 2024
text-classification
Introduction of roberta_first_toxicity_classifier
Model Details of roberta_first_toxicity_classifier
Toxicity Classification Model (but for the first part of the data)
This model is trained for toxicity classification task. The dataset used for training is the merge of the English parts of the three datasets by Jigsaw ( Jigsaw 2018 , Jigsaw 2019 , Jigsaw 2020 ), containing around 2 million examples. We split it into two parts and fine-tune a RoBERTa model ( RoBERTa: A Robustly Optimized BERT Pretraining Approach ) on it. THIS MODEL WAS FINE-TUNED ON THE FIRST PART. The classifiers perform closely on the test set of the first Jigsaw competition, reaching the AUC-ROC of 0.98 and F1-score of 0.76.
How to use
from transformers import RobertaTokenizer, RobertaForSequenceClassification
# load tokenizer and model weights, but be careful, here we need to use auth token
tokenizer = RobertaTokenizer.from_pretrained('SkolkovoInstitute/roberta_toxicity_classifier', use_auth_token=True)
model = RobertaForSequenceClassification.from_pretrained('SkolkovoInstitute/roberta_toxicity_classifier', use_auth_token=True)
# prepare the input
batch = tokenizer.encode('you are amazing', return_tensors='pt')
# inference
model(batch)
Licensing Information
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License .
Runs of s-nlp roberta_first_toxicity_classifier on huggingface.co
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More Information About roberta_first_toxicity_classifier huggingface.co Model
Url of roberta_first_toxicity_classifier
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Other API from s-nlp
Updated:November 08 2024
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