Text Classification
Transformers
Safetensors
PyTorch
English
Serbian
xlm-roberta
hate-speech-detection
multilingual
serbian
english
text-embeddings-inference
Instructions to use sadjava/multilingual-hate-speech-xlm-roberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sadjava/multilingual-hate-speech-xlm-roberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sadjava/multilingual-hate-speech-xlm-roberta")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sadjava/multilingual-hate-speech-xlm-roberta") model = AutoModelForSequenceClassification.from_pretrained("sadjava/multilingual-hate-speech-xlm-roberta") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 37f3c249562e9d4171c0e895a04df981dc4ff8f7b9ef32e8280570c57cfb2d05
- Size of remote file:
- 1.11 GB
- SHA256:
- a110841fd526a364b21e8ffa8965531a43018b2ebcf7c3fca6510898ab90179e
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