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")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MilaNLProc/hate-ita") model = AutoModelForSequenceClassification.from_pretrained("MilaNLProc/hate-ita") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d016c1126bc908cf8753fb95d0a3f2c7479ad45a22669fcff854b87e632784cd
- Size of remote file:
- 1.11 GB
- SHA256:
- e5ca0784add279d92ed2e44d2aeee1d81d2e0e6c3aed5d6c5ca44ce8d05e556e
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