| | --- |
| | license: cc-by-sa-4.0 |
| | tags: |
| | - hate-speech |
| | - toxic-comments |
| | - classification |
| | - hatebert |
| | - jigsaw |
| | - fine-tuned |
| | base_model: GroNLP/hateBERT |
| | datasets: |
| | - jigsaw-toxic-comment-classification-challenge |
| | metrics: |
| | - accuracy |
| | - f1 |
| | --- |
| | |
| | # HateBERT Fine-Tuned on Jigsaw Toxic Comments |
| |
|
| | This model is a fine-tuned version of [GroNLP/hateBERT](https://huggingface.co/GroNLP/hateBERT) on the [Jigsaw Toxic Comment Classification Challenge](https://www.kaggle.com/c/jigsaw-toxic-comment-classification-challenge) dataset. |
| |
|
| | ## How to Use |
| |
|
| | ```python |
| | from transformers import AutoModelForSequenceClassification, AutoTokenizer |
| | |
| | model = AutoModelForSequenceClassification.from_pretrained("Jensvollends/hatebert-finetuned") |
| | tokenizer = AutoTokenizer.from_pretrained("Jensvollends/hatebert-finetuned") |
| | |
| | inputs = tokenizer("You are a bad person", return_tensors="pt") |
| | outputs = model(**inputs) |
| | |
