Skip to main content
ML models depend on external libraries, data files, and specific hardware configurations. This guide shows you how to configure your model’s dependencies and resources. The config.yaml file defines your model’s configuration. Common options include:

​
Environment variables

To set environment variables in the model serving environment, use the environment_variables key:
config.yaml
environment_variables:
  MY_ENV_VAR: my_value

​
Python packages

Python packages can be specified in two ways in the config.yaml file:
  1. requirements: A list of Python packages to install.
  2. requirements_file: A requirements.txt file to install pip packages from.
To specify Python packages as a list, use the following:
config.yaml
requirements:
  - package_name
  - package_name2
Pin package versions using the == operator:
config.yaml
requirements:
  - package_name==1.0.0
  - package_name2==2.0.0
If you need more control over the installation process and want to use different pip options or repositories, you can specify a requirements_file instead.
config.yaml
requirements_file: ./requirements.txt

​
System packages

Truss also has support for installing apt-installable Debian packages. To add system packages to your model serving environment, add the following to your config.yaml file:
config.yaml
system_packages:
  - package_name
  - package_name2
For example, to install Tesseract OCR:
config.yaml
system_packages:
  - tesseract-ocr

​
Resources

Specify hardware resources in the resources section. Option 1: Specify individual resource fields For a CPU model:
config.yaml
resources:
  cpu: "1"
  memory: 2Gi
For a GPU model:
config.yaml
resources:
  accelerator: "L4"
When you push your model, it will be assigned an instance type matching the specifications required. Option 2: Specify an exact instance type
config.yaml
resources:
  instance_type: "L4:4x16"
Using instance_type lets you select an exact SKU. When specified, other resource fields are ignored. See the Resources page for more information on options available.

​
Advanced configuration

There are numerous other options for configuring your model. See some of the other guides: