Instructions to use IMSyPP/hate_speech_it with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IMSyPP/hate_speech_it with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="IMSyPP/hate_speech_it")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("IMSyPP/hate_speech_it") model = AutoModelForSequenceClassification.from_pretrained("IMSyPP/hate_speech_it", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| widget: | |
| - text: "Ciao, mi chiamo Marcantonio, sono di Roma. Studio informatica all'Università di Roma." | |
| language: | |
| - it | |
| license: mit | |
| # Hate Speech Classifier for Social Media Content in Italian Language | |
| A monolingual model for hate speech classification of social media content in Italian language. The model was trained on 119,670 YouTube comments and tested on an independent test set of 21,072 YouTube comments. It is based on Italian ALBERTO pre-trained language model. | |
| ## Please cite: | |
| Kralj Novak, P., Scantamburlo, T., Pelicon, A., Cinelli, M., Mozetič, I., & Zollo, F. (2022, July). __Handling disagreement in hate speech modelling__. In International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (pp. 681-695). Cham: Springer International Publishing. | |
| https://link.springer.com/chapter/10.1007/978-3-031-08974-9_54 | |
| ## Tokenizer | |
| During training the text was preprocessed using the original Italian ALBERTO tokenizer. We suggest the same tokenizer is used for inference. | |
| ## Model output | |
| The model classifies each input into one of four distinct classes: | |
| * 0 - acceptable | |
| * 1 - inappropriate | |
| * 2 - offensive | |
| * 3 - violent |