Text Classification
Transformers
PyTorch
Italian
xlm-roberta
text classification
abusive language
hate speech
offensive language
text-embeddings-inference
Instructions to use MilaNLProc/hate-ita with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MilaNLProc/hate-ita with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MilaNLProc/hate-ita")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MilaNLProc/hate-ita") model = AutoModelForSequenceClassification.from_pretrained("MilaNLProc/hate-ita", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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- offensive language
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widget:
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- text: "
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example_title: "Hate Speech Classification 1"
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- text: "Sei una testa di cazzo!!"
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example_title: "Hate Speech Classification 2"
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# HATE-ITA Base
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HATE-ITA is a binary hate speech classification model for Italian social media text.
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<img src="https://raw.githubusercontent.com/MilaNLProc/hate-ita/main/hateita.png?token=
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## Abstract
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- offensive language
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widget:
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- text: "Ci sono dei bellissimi capibara!"
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example_title: "Hate Speech Classification 1"
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- text: "Sei una testa di cazzo!!"
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example_title: "Hate Speech Classification 2"
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# HATE-ITA Base
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HATE-ITA is a binary hate speech classification model for Italian social media text.
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<img src="https://raw.githubusercontent.com/MilaNLProc/hate-ita/main/hateita.png?token=GHSAT0AAAAAABTEBAJ4PNDWAMU3KKIGUOCSYWG4IBA" width="200">
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## Abstract
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