Shieldgemma 2B - Details

Shieldgemma 2B, developed by Google, is a large language model with 2B parameters. It operates under the Gemma Terms of Use license and is designed for safe content moderation.

Shieldgemma is a series of safety content moderation models built upon Gemma 2, designed to address four key harm categories: sexually explicit content, dangerous content, hate, and harassment. It is a text-to-text, decoder-only large language model available in English with open weights. The series includes three parameter sizes: 2B, 9B, and 27B, offering flexibility for different use cases while prioritizing safe and responsible content moderation.

Shieldgemma 2B has 2B parameters, placing it in the small model category, which ensures fast and resource-efficient performance ideal for simple tasks. Its 4K context length falls under short contexts, making it suitable for brief interactions but limiting its ability to handle extended or complex text sequences. This combination prioritizes accessibility and speed while maintaining effectiveness for targeted content moderation.

• Name: Shieldgemma 2B
• Parameter Size: 2B
• Context Length: 4K
• Implications: Small parameter size enables efficiency, while 4K context length supports concise tasks but restricts handling of longer texts.

Shieldgemma 2B is designed for safety content moderation, with possible applications in filtering user-generated content, monitoring model-generated outputs, and combining both approaches for comprehensive oversight. Its 2B parameter size and 4K context length make it suitable for possible scenarios where real-time analysis of shorter texts is required, such as moderating chat interactions, social media posts, or collaborative platforms. However, these possible uses would need careful evaluation to ensure alignment with specific requirements, as the model’s architecture and training focus may influence its effectiveness in different contexts. The intended purpose of Shieldgemma 2B is to address harm categories like sexually explicit, dangerous, hate, and harassment content, but possible implementations should be tested thoroughly to confirm suitability for particular tasks.

• safety content moderation for human user inputs
• safety content moderation for model outputs
• combined safety content moderation for both inputs and outputs

Shieldgemma 2B is a safety-focused model with possible applications in areas like moderating user-generated content, filtering model outputs for harmful language, enhancing platform safety protocols, and supporting content policy enforcement. These possible uses could include analyzing text for harmful patterns, flagging inappropriate language, or assisting in automated content review workflows. However, possible implementations would require thorough testing to ensure alignment with specific needs, as the model’s design prioritizes safety over general-purpose tasks. The 2B parameter size and 4K context length make it suitable for possible scenarios involving shorter texts, but possible limitations may arise in complex or extended interactions.

• safety content moderation for human user inputs
• safety content moderation for model outputs
• combined safety content moderation for both inputs and outputs

Shieldgemma 2B’s medium q4 version requires a GPU with at least 8GB VRAM for efficient operation, making it suitable for systems with moderate hardware capabilities. This quantized variant balances precision and performance, allowing deployment on devices without high-end GPUs. However, possible variations in resource needs may depend on workload and implementation.

• fp16, q2, q3, q4, q5, q6, q8

Shieldgemma 2B, developed by Google, is a safety-focused large language model with 2B parameters and a 4K context length, designed for safe content moderation across user inputs and model outputs. It operates under the Gemma Terms of Use license, offers open weights, and is available in multiple sizes to balance efficiency and effectiveness in harm detection.

Huggingface Model Page
Ollama Model Page