# Best Practices for Efficient LLM Training

## post by mueller25 on Jul 20, 2024

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.

2. **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!