granite3-guardian

The IBM Granite Guardian 3.0 2B and 8B models are designed to detect risks in prompts and/or responses.

2b 8b

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Granite guardian models

The IBM Granite Guardian 3.0 2B and 8B models are designed to detect risks in prompts and/or responses. They can help with risk detection along many key dimensions catalogued in the IBM AI Risk Atlas. They are trained on unique data comprising human annotations and synthetic data informed by internal red-teaming, and they outperform other open-source models in the same space on standard benchmarks.

Parameter Sizes

The model will produce a single output token, either Yes or No. By default, the general-purpose harm category is used, but other categories can be selected by setting the system prompt.

2B:

ollama run granite3-guardian:2b
>>> /set system profanity

8B:

ollama run granite3-guardian:8b
>>> /set system violence

Supported Uses

  • Risk detection in prompt text or model response (i.e. as guardrails), such as:

    • Harm (harm): content considered generally harmful
    • Social Bias (social_bias): prejudice based on identity or characteristics
    • Jailbreaking (jailbreak): deliberate instances of manipulating AI to generate harmful, undesired, or inappropriate content
    • Violence (violence): content promoting physical, mental, or sexual harm
    • Profanity (profanity): use of offensive language or insults
    • Sexual Content (sexual_content): explicit or suggestive material of a sexual nature
    • Unethical Behavior (unethical_behavior): actions that violate moral or legal standards

  • RAG (retrieval-augmented generation) to assess:

    • Context relevance (relevance): whether the retrieved context is relevant to the query
    • Groundedness (groundedness): whether the response is accurate and faithful to the provided context
    • Answer relevance (answer_relevance): whether the response directly addresses the user’s query

Granite dense models

The Granite dense models are available in 2B and 8B parameter sizes designed to support tool-based use cases and for retrieval augmented generation (RAG), streamlining code generation, translation and bug fixing.

See model page

Granite mixture of experts models

The Granite MoE models are available in 1B and 3B parameter sizes designed for low latency usage and to support deployment in on-device applications or situations requiring instantaneous inference.

See model page

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