Quick Deployment of LLaMA2 Model

Introduction

The LLaMA2 model has undergone broader and deeper training, featuring a greater number of tokens and a longer context length. Compared to LLaMA 1, LLaMA2 has been trained with 2 trillion tokens and its context length is double that of LLaMA1. In addition, the LLaMA-2-chat model has also been trained with over a million new human annotations. The training corpus of the LLaMA2 model is richer than that of the LLaMA 1, with 40% more data. Its context length has been upgraded from 2048 to 4096, enabling it to understand and generate longer text and provide better support for more complex tasks. The distribution of languages in the pre-training data accounts for percentages greater than or equal to 0.005%, but the majority of the data is in English, therefore LLaMA2 performs best in English use cases. If you want to use LLaMA2 for copy planning in a Chinese context, additional Chinese enhancement training is required to make it perform even better when processing Chinese text.

Quick Deployment

Log in to the UCloud Global console (https://console.ucloud-global.com/uhost/uhost/create), select “GPU Type” for the model type, and “V100S.” Choose the detailed configurations such as the number of CPU and GPU cores as needed.
Minimum recommended configuration: 10-core CPU 64G memory 1 V100S.
Select “Image Market” for the image, search for “LLaMA2” in the image name, and select this image to create the GPU cloud host.
Once the GPU cloud host is successfully created, log in to the GPU cloud host.