guild.yml to your TensorFlow or Keras project to
automate tasks and enable experiment tracking,
testing, distribution and remote training.
Train your model by running the command
run train to generate a unique experiment that preserves
training files and metadata.
Capture results as unique experiments by running operations—compare performance, diff changes, visualize with TensorBoard and backup to the cloud. Learn more.
Automate your model life cycle from data collection and pre-processing to training and evaluation to optimization and deployment. Learn more.
Verify all stages of your model workflow with tests that exercise code and check results such as expected loss and accuracy ranges. Learn more.
As you run operations, Guild automatically captures run logs and files so you can study and compare them. Guild seamlessly indexes TensorFlow event logs to capture training and evaluation metrics, letting you quickly view model performance across runs.