| language: | |
| - en | |
| tags: | |
| - toxic text classification | |
| licenses: | |
| - apache-2.0 | |
| ## Toxicity Classification Model | |
| This model is trained for toxicity classification task using. The dataset used for training is the dataset by **Jigsaw** ( [Jigsaw 2020](https://www.kaggle.com/c/jigsaw-multilingual-toxic-comment-classification)). We split it into two parts and fine-tune a DistilBERT model ([DistilBERT base model (uncased) ](https://huggingface.co/distilbert-base-uncased)) on it. DistilBERT is a distilled version of the [BERT base model](https://huggingface.co/bert-base-uncased). It was introduced in this [paper](https://arxiv.org/abs/1910.01108). | |
| ## How to use | |
| ```python | |
| from transformers import pipeline | |
| text = "This was a masterpiece. Not completely faithful to the books, but enthralling from beginning to end. Might be my favorite of the three." | |
| classifier = pipeline("text-classification", model="tensor-trek/distilbert-toxicity-classifier") | |
| classifier(text) | |
| ``` | |
| ## License | |
| [Apache 2.0](./LICENSE) |