If you’re developing with large language models (LLMs), you may find yourself stuck in a loop of “vibe testing,” where prompt adjustments yield unpredictable outputs. This uncertainty stems from the non-deterministic nature of AI models, complicating traditional testing methods like unit tests. To streamline LLM evaluation, we’ve created Stax, an innovative developer tool that simplifies the evaluation process, combining insights from Google DeepMind and Google Labs. Stax enables you to establish custom AI evaluations tailored to your specific use case, contrasting with generic benchmarks. Utilizing both human labeling and autoraters powered by advanced LLMs, Stax grants you the tools to assess coherence, factuality, and tone efficiently. You can easily upload datasets or create them from scratch, build custom autoraters, and define your unique evaluation criteria. Elevate your LLM features from guesswork to data-driven confidence. Start evaluating with Stax today at stax.withgoogle.com and engage with us on Discord for feedback!
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