Instructions to use IMSyPP/hate_speech_nl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IMSyPP/hate_speech_nl with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="IMSyPP/hate_speech_nl")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("IMSyPP/hate_speech_nl") model = AutoModelForSequenceClassification.from_pretrained("IMSyPP/hate_speech_nl", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from IMSyPP/hate_speech_nl: direct link, hf CLI and curl.
- Browser
- Download file 716 Bytes
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https://huggingface.co/IMSyPP/hate_speech_nl/resolve/main/README.md
- Command line
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hf download hf://IMSyPP/hate_speech_nl/README.md
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curl -L -o README.md https://huggingface.co/IMSyPP/hate_speech_nl/resolve/main/README.md
716 Bytes
metadata
language:
- nl
license: mit
Hate Speech Classifier for Social Media Content in Dutch
A monolingual model for hate speech classification of social media content in Dutch. The model was trained on 20000 social media posts (youtube, twitter, facebook) and tested on an independent test set of 2000 posts. It is based on thepre-trained language model BERTje.
Tokenizer
During training the text was preprocessed using the BERTje 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