Granite3 Guardian 2B - Details

Granite3 Guardian 2B is a large language model developed by Ibm Granite, featuring 2b parameters under the Apache License 2.0. It is designed to focus on risk detection in prompts and responses with comprehensive guardrails.

Granite3 Guardian 2B is a fine-tuned Granite 3.0 2B Instruct model optimized for risk detection in prompts and responses. It leverages the IBM AI Risk Atlas to address risks across multiple dimensions and is trained on human annotations and synthetic data informed by internal red-teaming. This model outperforms other open-source alternatives on standard benchmarks while operating under the Apache License 2.0. Developed by Ibm Granite, it emphasizes robust guardrails to mitigate potential harms in AI interactions.

Granite3 Guardian 2B has 2b parameters, placing it in the small model category, which ensures fast and resource-efficient performance for targeted tasks like risk detection. Its 4k context length falls under short contexts, making it suitable for analyzing prompts and responses without excessive resource demands. This configuration balances efficiency with the ability to handle moderate complexity while prioritizing safety through guardrails. The model’s design emphasizes precision in risk assessment, leveraging its parameter size and context length to maintain responsiveness without compromising on security.

• Name: Granite3 Guardian 2B
• Parameter_Size: 2b
• Context_Length: 4k
• Implications: Small parameter size ensures efficiency, while 4k context length supports focused risk analysis without overburdening resources.

Granite3 Guardian 2B is designed for detecting harm-related risks within prompt text or model responses, offering possible applications in scenarios where safety and alignment are critical. Its possible use in retrieval-augmented generation (RAG) could involve assessing context relevance, groundedness, and answer relevance to ensure generated content aligns with provided sources. These possible uses highlight its role in refining AI interactions by identifying potential issues early, though further investigation is needed to validate effectiveness in specific contexts. The model’s focus on guardrails suggests possible value in environments requiring careful oversight, but its deployment should be thoroughly evaluated before application.

• Intended_Uses: detecting harm-related risks within prompt text or model response
• Intended_Uses: rag (retrieval-augmented generation) use-case where the guardian model assesses context relevance, groundedness, and answer relevance

Granite3 Guardian 2B is a model with possible applications in scenarios requiring careful oversight of generated content, such as possible use in content moderation to identify harmful or inappropriate language. It could also serve as a possible tool for enhancing model transparency by evaluating the relevance and alignment of responses in retrieval-augmented generation workflows. Possible deployment in collaborative writing environments might involve assessing the groundedness of generated text to ensure it aligns with provided sources. Additionally, it could support possible integration into interactive systems where real-time risk assessment of user inputs or outputs is needed. Each of these possible applications requires thorough evaluation and testing to ensure alignment with specific use cases and ethical standards before implementation.

• Possible application: content moderation to identify harmful language
• Possible application: enhancing transparency in retrieval-augmented generation
• Possible application: assessing groundedness of generated text in collaborative tools
• Possible application: real-time risk assessment in interactive systems

Granite3 Guardian 2B in its medium q4 version requires a GPU with at least 12GB VRAM for efficient operation, balancing precision and performance. This configuration is suitable for systems with multi-core CPUs and 32GB+ RAM, ensuring smooth execution without excessive resource strain. While possible applications may vary, the hardware needs depend on the specific quantization used.

• Quantizations: fp16, q5, q6, q8

Granite3 Guardian 2B is a 2b-parameter model developed by Ibm Granite under the Apache License 2.0, designed to detect risks in prompts and responses with robust guardrails. It leverages specialized training data and outperforms open-source alternatives in risk assessment tasks, making it suitable for applications requiring safety-focused oversight.

Huggingface Model Page
Ollama Model Page