Shypd.aiThe largest open index of AI toolsAutolabel is a Data Labeling & Annotation tool that labels, cleans, and enriches text datasets using Large Language Models (LLMs). It helps prepare large, clean, and diverse labeled datasets for machine learning efforts.
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Autolabel is a Python library designed to label, clean, and enrich text datasets using various Large Language Models (LLMs). It supports both commercial and open-source LLMs from providers like OpenAI, Anthropic, HuggingFace, and Google. The tool streamlines the data labeling process into a simple 3-step workflow: defining labeling guidelines and the LLM model in a JSON config, dry-running to verify the prompt, and then executing the labeling run on the dataset. Autolabel incorporates research-proven LLM techniques such as few-shot learning and chain-of-thought prompting to enhance label quality. It also provides confidence estimation and explanations for each output label, along with caching and state management to minimize costs and experimentation time. Additionally, Refuel offers hosted LLMs for labeling and confidence estimation, allowing users to calibrate confidence thresholds and route less confident labels for human review.
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