Text Classification
Transformers
Safetensors
xlm-roberta
prompt-injection
security
llm-security
Eval Results (legacy)
text-embeddings-inference
Instructions to use daniel315a/xlm-roberta-prompt-injection-multilingual with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use daniel315a/xlm-roberta-prompt-injection-multilingual with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="daniel315a/xlm-roberta-prompt-injection-multilingual")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("daniel315a/xlm-roberta-prompt-injection-multilingual") model = AutoModelForSequenceClassification.from_pretrained("daniel315a/xlm-roberta-prompt-injection-multilingual") - Notebooks
- Google Colab
- Kaggle
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