Best Practices for Efficient LLM Training

Technical Help
1

Hello everyone,

I’m relatively new to Lambda and I’m looking to optimize my workflow for training large language models (LLMs). Currently, I encounter a couple of issues that slow down the process:

  1. Setting Up the Environment:
  • I have to install conda and create a new conda environment every time I launch a new instance. This setup process is time-consuming.
  1. Downloading LLMs:
  • Downloading the models takes significant time as well.

I’m curious about the best practices that others in the community follow to streamline these processes. Specifically, I have a few questions:

  • Is there a common way to handle environment setup more efficiently?
  • What methods do you use to speed up model downloads?
  • Would Docker be a viable solution for these issues, or are there better alternatives?

Any insights, tips, or recommendations on how to make these processes faster and more efficient would be greatly appreciated. Thank you!