Text Classification
Transformers
PyTorch
English
bert
BERTicelli
text classification
abusive language
hate speech
offensive language
Instructions to use patrickquick/BERTicelli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use patrickquick/BERTicelli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="patrickquick/BERTicelli")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("patrickquick/BERTicelli") model = AutoModelForSequenceClassification.from_pretrained("patrickquick/BERTicelli") - Notebooks
- Google Colab
- Kaggle
| language: | |
| - en | |
| tags: | |
| - BERTicelli | |
| - text classification | |
| - abusive language | |
| - hate speech | |
| - offensive language | |
| datasets: | |
| - OLID | |
| license: apache-2.0 | |
| widget: | |
| - text: "If Jamie Oliver fucks with my £3 meal deals at Tesco I'll kill the cunt." | |
| example_title: "Example 1" | |
| - text: "Keep up the good hard work." | |
| example_title: "Example 2" | |
| - text: "That's not hair. Those were polyester fibers because Yoda is (or was) a puppet." | |
| example_title: "Example 3" | |
| [Mona Allaert](https://github.com/MonaDT) • | |
| [Leonardo Grotti](https://github.com/corvusMidnight) • | |
| [Patrick Quick](https://github.com/patrickquick) | |
| ## Model description | |
| BERTicelli is an English pre-trained BERT model obtained by fine-tuning the [English BERT base cased model](https://github.com/google-research/bert) with the training data from [Offensive Language Identification Dataset (OLID)](https://scholar.harvard.edu/malmasi/olid). | |
| This model was developed for the NLP Shared Task in the Digital Text Analysis program at the University of Antwerp (2021–2022). |