@@ -79,19 +79,38 @@ deploy_options = model.list_deploy_options()
7979
8080** Use case:** Evaluate compatible machine specs and containers before deployment.
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82- ## Customize Deployment: Machine and Resource Configuration
82+ ## Select a Verified Deployment: By Container Image
8383
84- Specify exact hardware resources and endpoint/model names .
84+ Specify a container image from the list of verified deployment configurations .
8585
8686``` python
8787endpoint = model.deploy(
88- machine_type = " g2-standard-4" ,
89- accelerator_type = " NVIDIA_L4" ,
88+ serving_container_image_uri = " us-docker.pkg.dev/vertex-ai/vertex-vision-model-garden-dockers/pytorch-vllm-serve:20250430_0916_RC00_maas" ,
89+ )
90+ ```
91+
92+ ## Select a Verified Deployment: By Hardware
93+
94+ Specify a hardware configuration from the list of verified deployment configurations.
95+
96+ ``` python
97+ endpoints = model.deploy(
98+ machine_type = " a3-highgpu-1g" ,
99+ accelerator_type = " NVIDIA_H100_80GB" ,
100+ accelerator_count = 1 ,
101+ )
102+ ```
103+
104+ ## Select a Verified Deployment: By Container and Hardware
105+
106+ Specify both a container image and a hardware configuration from the list of verified deployment configurations.
107+
108+ ``` python
109+ endpoint = model.deploy(
110+ serving_container_image_uri = " us-docker.pkg.dev/vertex-ai/vertex-vision-model-garden-dockers/pytorch-vllm-serve:20250430_0916_RC00_maas" ,
111+ machine_type = " a3-highgpu-1g" ,
112+ accelerator_type = " NVIDIA_H100_80GB" ,
90113 accelerator_count = 1 ,
91- min_replica_count = 1 ,
92- max_replica_count = 1 ,
93- endpoint_display_name = " paligemma-endpoint" ,
94- model_display_name = " paligemma-model"
95114)
96115```
97116
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