When you deploy certain assets in watsonx.ai Runtime, you can choose the type, size, and power of the hardware configuration that matches your computing needs.
Creating hardware specifications for deployments
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You can create hardware specifications for your deployments in the following ways:
Python client library: Use the hardware_specifications.store function from the Python client library. For more information, see Python client library reference
Data and AI Common Core API: Use POST /v2/hardware_specifications from the Environments list in the Data and AI Common Core API to create a hardware specification. For more information, see Environments API reference.
Deployment types that require hardware specifications
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Selecting a hardware specification is available for all batch deployment types. For online deployments, you can select a specific hardware
specification if you're deploying:
Python Functions
Tensorflow models
Models with custom software specifications
Hardware configurations available for deploying assets
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XS: 1x4 = 1 vCPU and 4 GB RAM
S: 2x8 = 2 vCPU and 8 GB RAM
M: 4x16 = 4 vCPU and 16 GB RAM
L: 8x32 = 8 vCPU and 32 GB RAM
XL: 16x64 = 16 vCPU and 64 GB RAM
You can use the XS configuration to deploy:
Python functions
Python scripts
R scripts
Models based on custom libraries and custom images
For Decision Optimization deployments, you can use these hardware specifications:
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