AWS Inferentia2 Accelerates Llama 2 Inference

It covers how to efficiently deploy LLMs such as Llama 2 on AWS Inferentia2 instances and maximize inference performance using Hugging Face's optimum-neuron library.

Key implementation steps:

• Environment setup: You can easily install the required libraries by using the Neuron Deep Learning AMI (DLAMI) provided by Hugging Face, or via the DLC for SageMaker.
• Model compilation and export: Using the optimum-neuron API, a standard Transformers model is compiled into the Neuron-specific format. At this point, you can specify the number of cores to use and the data precision (fp16, etc.), and the compiled model can be saved to the Hugging Face Hub for reuse.
• Text generation: The compiled model can generate text in the same way as the existing Transformers library, via NeuronModelForCausalLM.