TLDR We trained a series of 7B LLMs named XGen-7B with standard dense attention on up to 8K sequence length for up to 1.5T tokens. We also fine tune the models on public-domain instructional data. The main take-aways are: * On standard NLP benchmarks, XGen achieves comparable or better results

TL;DR: Slack is a powerful productivity tool that professionals and teams around the globe depend on to communicate and keep up with vital information at work, making async work efficient. However, with an increase in the number (and variety) of conversations on Slack that a typical user keeps track

How many emails and working-related conversations do you have every day? The average office worker receives about 121 emails [https://www.campaignmonitor.com/blog/email-marketing/2019/05/shocking-truth-about-how-many-emails-sent/] daily and uncountable messages on platforms such as Slack [https://slack.com/], Team [https://www.microsoft.com/en-us/microsoft-teams/group-chat-software], or iMessage