About training jobs

Use jobs to retrain models on a regular basis. Jobs can be created from notebooks or git.

Jobs run in the same environment as the deployment, using the same Python and system packages.

Visit the Training Jobs page within your deployment to view previous executions of jobs, how long each job took, and any logs output created by the job.

Creating jobs from a notebook

You can create jobs and add them to deployments from your Python notebook with the mb.add_job(...) command. Follow the creating jobs from a notebook section to learn more.

Creating jobs from git

Jobs are defined in a jobs.yaml file, within each deployment's directory. Follow the creating jobs with git section to learn more.

Runner sizes

Jobs can be run on different size job runners. By default, jobs run on the small runner size.

Runner Size	CPUs	GB RAM	Cost Factor
small	2	15	1
medium	4	30	2
large	8	60	4
xlarge	16	120	8
2xlarge	32	240	16
4xlarge	64	480	32

GPU Runners

Training jobs using GPU Runners have access to an NVIDIA T4 or A10G GPU, in addition to the CPU and RAM below.

Runner Size	CPUs	GB RAM	GPU	GB VRAM	Cost Factor
gpu_small	4	15	T4	16	1
gpu_medium	16	60	A10G	24	5
gpu_large	32	120	A10G	24	8

See the notebook or git jobs documentation for how to use different size job runners.