Dolphin - Efficient Data Curation at Cognitive Computations with Cerebras - Cerebras

This post details how Cerebras inference was used to accelerate data curation for training the Dolphin LLM models. It highlights a 90% reduction in processing time and a 10x increase in tokens per second (from 100 to 1,000), enabling the processing of millions of samples in two days instead of a month. The system's ability to handle concurrent requests improved from 20 to 200 requests per minute. The post emphasizes the rapid, nuanced classification of complex conversation samples within milliseconds to filter out unwanted content, contributing to improved AI model quality and faster iteration cycles.