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 config.json
Browse files- config.json +2 -2
config.json
CHANGED
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@@ -38,7 +38,7 @@
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"hateful": 1
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},
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"id2label": {
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0: "non-hateful",
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1: "hateful"
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}
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}
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"hateful": 1
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},
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"id2label": {
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"0": "non-hateful",
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"1": "hateful"
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}
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}
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