Text Classification
Transformers
Safetensors
modernbert
llm-security
prompt-injection
jailbreak
jailbreak-detection
guardrail
multilingual
sequence-classification
Eval Results (legacy)
text-embeddings-inference
Instructions to use NeuralTrust/prompt-guard-oss-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NeuralTrust/prompt-guard-oss-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="NeuralTrust/prompt-guard-oss-small")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("NeuralTrust/prompt-guard-oss-small") model = AutoModelForSequenceClassification.from_pretrained("NeuralTrust/prompt-guard-oss-small", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4979ea4051b704efcb2a1a34961c5f93d2fa004f33c607d894c7ebe32511f588
- Size of remote file:
- 34.4 MB
- SHA256:
- f34b44a6dc8a0eef651bfa10e8325057530152606a69d9c3b6ae02efb1558f0a
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