ModernBERT PromptGuard is a high-performance binary classifier specifically designed to detect malicious prompts in large language model applications, including prompt injection and jailbreak attacks.

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Llama Prompt Guard 2 is a series of prompt attack detection models launched by Meta, including an upgraded 86M-parameter version and a lightweight 22M-parameter version, designed to detect prompt injection and jailbreak attacks in large language model applications.

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Llama Prompt Guard 2 86M is a text classification model designed to detect prompt injection and jailbreak attacks, serving as the second-generation product in the Prompt Guard series.

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PIGuard is a new type of prompt protection model specifically designed to detect prompt injection attacks. Through an innovative training strategy, it significantly reduces the bias towards trigger words, performs excellently in multiple benchmark tests, surpassing the current best model by 30.8%, and provides a powerful open-source protection solution for LLM security.

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InjecGuard is a protective model against prompt injection attacks for large language models (LLMs), capable of effectively identifying and defending against malicious instructions while reducing over-defense issues.

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A prompt injection detection model fine-tuned based on microsoft/mdeberta-v3-base, trained with multiple datasets to identify malicious prompt injection attacks.

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A lightweight model based on ModernBERT, focused on identifying malicious prompt injection attacks and providing AI security protection.

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A lightweight model based on ModernBERT (large model edition), specifically designed to identify malicious prompts (i.e., prompt injection attacks).

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Prompt Guard is a text classification model designed to detect prompt attacks, capable of identifying malicious prompt injections and jailbreak attempts.

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TestSavantAI models are a set of fine-tuned classifiers specifically designed to defend against prompt injection and jailbreak attacks targeting large language models (LLMs).

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The TestSavantAI model is a set of classifiers specifically designed to defend against prompt injection and jailbreak attacks in large language models (LLMs). The tiny version is based on the BERT-tiny architecture, balancing security and computational efficiency.

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GenTel-Shield is a model focused on detecting and defending against prompt injection attacks, effectively distinguishing malicious samples from benign ones.

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PromptGuard is a text classification model designed to detect and protect against LLM prompt attacks, capable of identifying malicious prompt injections and jailbreak attempts.

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This is the ONNX format conversion of the fmops/distilbert-prompt-injection model, designed for detecting prompt injection attacks.

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This is the ONNX-converted version of the deepset/deberta-v3-base-injection model for detecting prompt injection attacks.

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Dataset for detecting and preventing prompt injection attacks, supporting multilingual text analysis

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