Can I use custom principles with this skill?

Yes, the skill is designed to work with custom constitutions, allowing you to define specific rules for tone, domain-specific safety, or specialized behavior for your agent.

How does RLAIF differ from RLHF?

RLAIF (Reinforcement Learning from AI Feedback) uses an AI model to evaluate and rank responses based on a constitution, making it more scalable and less costly than traditional RLHF which relies on human annotators.

What is Constitutional AI?

Constitutional AI is a method developed by Anthropic to train AI models to be harmless and helpful by following a set of principles (a 'constitution'), using AI feedback rather than human labels.

Does this skill work with any model?

While optimized for models compatible with the Hugging Face ecosystem (Transformers, TRL), the principles of Constitutional AI can be applied to any capable LLM that can perform self-critique.

What are the hardware requirements for this skill?

For 7B parameter models, it is recommended to use at least one NVIDIA A100 (40GB) for the SL phase and two A100s for the RL phase to accommodate both the policy and reward models.

Constitutional AI Safety Alignment

Name: Constitutional AI Safety Alignment
Author: zechenzhangAGI

byzechenzhangAGI

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384

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Ciencia de Datos y ML

Implements Anthropic's Constitutional AI method to train harmless, helpful models through self-critique and automated AI feedback.

This skill provides a comprehensive framework for implementing Constitutional AI (CAI), a specialized approach for safety alignment that reduces harmful outputs without requiring manual human labeling. It guides developers through a robust two-phase process: first, supervised learning where models critique and revise their own responses based on a predefined 'constitution' of principles; and second, Reinforcement Learning from AI Feedback (RLAIF) to scale safety training. It is an essential toolkit for AI researchers and engineers aiming to build models that are not only safe but also explainable and nuanced in their decision-making processes.

Características Principales

01Automated self-critique and response revision workflows

02Seamless integration with Hugging Face TRL and Transformers

03Two-phase alignment featuring Supervised Learning and RLAIF

04Chain-of-thought reasoning for transparent safety critiques

05Scalable AI preference evaluation for reward model training

06384 GitHub stars

Casos de Uso

01Building safety-aligned internal LLMs without expensive human annotation teams

02Implementing scalable oversight via AI-led feedback loops in research environments

03Reducing model evasiveness while maintaining strict harmlessness standards

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add zechenzhangagi/ai-research-skills constitutional-ai

For use in Claude.ai and ChatGPT

Download Skill