Mixtral 8x7B is an open large language model (LLM) from Mistral AI built using a Mixture of Experts (MoE) architecture. It combines 8 separate "expert" models into one for more efficient and diverse language generation capabilities.
In this tutorial, we will walk through deploying the Mixtral 8x7B model on Amazon SageMaker using Hugging Face's Large Language Model Deep Learning Container (LLM DLC). The LLM DLC provides an optimized, scalable container environment specifically for serving large language models.
We will cover:
- Setting up the development environment
- Retrieving the LLM DLC image
- Hardware sizing considerations
- Deploying Mixtral 8x7B on SageMaker
- Invoking the model for inference
- Cleaning up resources By the end, you will have Mixtral 8x7B deployed on SageMaker and be able to interact with it via API calls.
- AWS account
- Some familiarity with SageMaker
- Python/Boto3 basics
Let's get started with setting up our environment!