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A d a p t a t i o n o f L a r g e F o u n d a t i o n M o d e l s A b o u t T h i s W h i t e p a p e r Tuning a lar ge model inv olv es adjusting and adapting a pre-tr ained model to per form specific tasks with the user provided training dataset. This white paper is a technical reference aimed at outlining Google 's a... |
able to push the boundaries of these models by scaling them up, leading to even mor e power ful and capable systems. This scalability enables foundation models to tackle incr easingly complex tasks and achie ve state-of-the-ar t per formance acr oss various domains. New gener ations of acceler ators (e. g. TPUs, GPUs) ... |
D e s i g n o f A d a p t e r T u n i n g o n V e r t e x A I Our Parameter Efficient Fine Tuning jobs run on Cloud TPUs/GPUs thr ough Vertex AI' s training ser vice. Vertex AI creates a separ ate tenant pr oject for each cust omer project and runs the training workloads on Compute Engine VMs on the tenant project. Durin... |
Cust omer-Managed Encr yption Keys (CMEK) on Cloud Storage and accessed via the user-pr ovided 2 ser vice account for enhanced security and inside the VPC security perimeter of the cust omer. Tempor ary checkpoints gener ated in the tenant' s project buck et are subject to aut omatic deletion within a 30-da y period, m... |
Security considerations The adapter layer is stored on Cloud Storage with the option of using CMEK, Access Transpar ency 3 with audit logging, and multi-par ty authentication for many of the administr ativ e processes. You can use VPC Ser vice Contr ols (VPC-SC ) to create a ser vice perimeter that protects the endpoin... |
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