Text Classification
Transformers
ONNX
Safetensors
deberta-v2
prompt-injection
jailbreak-detection
prompt-injection-detection
llm-security
guardrails
multilingual
mdeberta
text-embeddings-inference
Instructions to use bastionsoft/binary-bastion-prompt-protection-mdeberta-v3-base-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bastionsoft/binary-bastion-prompt-protection-mdeberta-v3-base-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="bastionsoft/binary-bastion-prompt-protection-mdeberta-v3-base-v1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("bastionsoft/binary-bastion-prompt-protection-mdeberta-v3-base-v1") model = AutoModelForSequenceClassification.from_pretrained("bastionsoft/binary-bastion-prompt-protection-mdeberta-v3-base-v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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