Installation & Setup


pip install labml

Create .labml.yaml file

check_repo_dirty: true
data_path: 'data'
experiments_path: 'logs'
analytics_path: 'analytics'

You need to create a .labml.yaml file at the root of your project. The values will default to above so an empty file should work for most of the use cases.

check_repo_dirty: If true, before running an experiment it checks and aborts if there are any uncommitted changes

data_path: The location of data files. this can be accessed via labml.lab.get_data_path().

experiments_path: This is where all the experiment details such as logs, configs and checkpoints are saved. This can be accessed via labml.lab.get_experiments_path().

analytics_path: ⚠️ This is where Jupyter Notebooks for custom analytics will be saved. This is still experimental.


You don’t need the .labml.yaml file if you only use labml.logger.


pip install labml-dashboard

Navigate to the path of the project and run the following command to start the server.

labml dashboard