data-annotation

What problem does it solve?

This Skill streamlines the creation, formatting, and validation of datasets essential for training and aligning AI models, particularly for instruction tuning and reinforcement learning from human feedback (RLHF).

Core Features & Use Cases

• Dataset Creation: Generate instruction-response pairs, multi-turn conversations, and preference datasets (chosen/rejected).
• Synthetic Data Generation: Leverage LLMs to create synthetic training data when manual annotation is insufficient.
• Quality Assurance: Implement validation checks for schema, duplicates, length, and toxicity.
• Use Case: A machine learning engineer needs to create a dataset of customer support dialogues for fine-tuning a chatbot. This skill can help generate realistic conversations, format them correctly, and ensure the quality of the data before training.

Quick Start

Use the data-annotation skill to create 100 instruction-response pairs for summarization tasks.