A useful but little-known OpenAI API feature 📊 Manually checking every model output for quality? There's a way to automate that. OpenAI's "Graders" automatically score model outputs. Use them for quality evaluation in Evals or as reward functions for reinforcement fine-tuning. 📌 Title: Graders 🔗 URL: 🧩 Overview Improving model quality requires a way to quantitatively judge what's good and what's bad. Graders are automatic scoring functions that evaluate model outputs. They support multiple methods: string matching, model-based judgment, custom Python code evaluation, and more. Use them in Evals pipelines for quality measurement or as reward functions for reinforcement fine-tuning. 🛠 How to use it Choose a scoring method and define your evaluation criteria. Options range from simple string matching and label checking to complex quality assessments using another LLM as a judge. Plug the grader into your Evals pipeline or use it as a reward signal for reinforcement fine-tuning. 🏗 Building it into production ・Continuous quality monitoring: sample production outputs and auto-score them with graders. Catch quality degradation early. ・Evals pipelines: quantitatively compare quality when changing prompts or updating models. ・Reinforcement fine-tuning: use grader scores as rewards to improve models through reinforcement learning. ・A/B test evaluation: compare outputs from different prompts or models using graders as the evaluation backbone. 💡 Use cases 📈 Continuous quality monitoring of model outputs 🧪 Quantitative quality comparison in Evals 🎯 Reward design for reinforcement fine-tuning 🔬 A/B testing of prompts and models ⚠️ Watch out The quality of your graders determines the reliability of your evaluations. Model-based graders in particular can produce inconsistent scores if the criteria are vague. Define clear, specific evaluation criteria and calibrate against human judgments to keep grading trustworthy. ✨ Quality improvement starts with measurement. Plug graders into your Evals pipeline and start quantifying output quality today. #OpenAI# #LLM#