video1.0<iframe src="https://www.loom.com/embed/e0d08fddf64e46d4b857c942e6111b00" frameborder="0" width="1248" height="936" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>9361248Loomhttps://www.loom.com9361248https://cdn.loom.com/sessions/thumbnails/e0d08fddf64e46d4b857c942e6111b00-00001.jpg171.901This video shows a demo of how you can use Refuel to quickly label data using LLMs. All you have to do is to upload your data, describe how you want your data labeled and let the LLM do the labeling for you. Here, we show a dataset containing user comments and Refuel is used to classify them as "toxic" or "not toxic". Why teams use Refuel: * Label 10,000+ data points in an hour vs weeks * Better-than-human labeling quality * Confidence scores, LLM benchmarking and fine-tuning for the highest levels of accuracy * Data connectors to read websites, perform web searches and ability to deploy as an endpoint to scale to millions examples seamlessly