Environment variables - CoreWeave

Fetch the complete documentation index at: /llms.txt Use this file to discover all available pages before exploring further. When you’re running a script in an automated environment, you can control Weights & Biases with environment variables set before the script runs or within the script. # This is secret and shouldn't be checked into version control WANDB_NOTES = "Smaller learning rate, more regularization." # Only needed if you don't check in the wandb/settings file # If you don't want your script to sync to the cloud # Add sweep ID tracking to Run objects and related classes os.environ[ "WANDB_SWEEP_ID" ] = "b05fq58z" Use these optional environment variables to do things like set up authentication on remote machines. Variable name Usage WANDB_API_KEY Sets the authentication key associated with your account. Create an API key at User Settings . This must be set if wandb login hasn’t been run on the remote machine. WANDB_BASE_URL If you’re using wandb/local you should set this environment variable to http://YOUR_IP:YOUR_PORT WANDB_CACHE_DIR This defaults to ~/.cache/wandb, you can override this location with this environment variable WANDB_CONFIG_DIR This defaults to ~/.config/wandb, you can override this location with this environment variable WANDB_CONFIG_PATHS Comma separated list of yaml files to load into wandb.config. See config . WANDB_CONSOLE Set this to “off” to disable stdout / stderr logging. This defaults to “on” in environments that support it. WANDB_DATA_DIR Where to upload staging artifacts. The default location depends on your platform, because it uses the value of user_data_dir from the platformdirs Python package. Make sure this directory exists and the running user has permission to write to it. WANDB_DIR Where to store all generated files. If unset, defaults to the wandb directory relative to your training script. Make sure this directory exists and the running user has permission to write to it. This does not control the location of downloaded artifacts, which you can set using the WANDB_ARTIFACT_DIR environment variable. WANDB_ARTIFACT_DIR Where to store all downloaded artifacts. If unset, defaults to the artifacts directory relative to your training script. Make sure this directory exists and the running user has permission to write to it. This does not control the location of generated metadata files, which you can set using the WANDB_DIR environment variable. WANDB_DISABLE_GIT Prevent wandb from probing for a git repository and capturing the latest commit / diff. WANDB_DISABLE_CODE Set this to true to prevent wandb from saving notebooks or git diffs. We’ll still save the current commit if we’re in a git repo. WANDB_DOCKER Set this to a docker image digest to enable restoring of runs. This is set automatically with the wandb docker command. You can obtain an image digest by running wandb docker my/image/name:tag --digest WANDB_ENTITY The entity associated with your run. If you have run wandb init in the directory of your training script, it will create a directory named wandb and will save a default entity which can be checked into source control. If you don’t want to create that file or want to override the file you can use the environmental variable. WANDB_ERROR_REPORTING Set this to false to prevent wandb from logging fatal errors to its error tracking system. WANDB_HOST Set this to the hostname you want to see in the wandb interface if you don’t want to use the system provided hostname WANDB_IGNORE_GLOBS Set this to a comma separated list of file globs to ignore. These files will not be synced to the cloud. WANDB_JOB_NAME Specify a name for any jobs created by wandb . WANDB_JOB_TYPE Specify the job type, like “training” or “evaluation” to indicate different types of runs. See grouping for more info. WANDB_MODE If you set this to “offline” wandb will save your run metadata locally and not sync to the server. If you set this to disabled wandb will turn off completely. WANDB_NAME The human-readable name of your run. If not set it will be randomly generated for you WANDB_NOTEBOOK_NAME If you’re running in jupyter you can set the name of the notebook with this variable. We attempt to auto detect this. WANDB_NOTES Longer notes about your run. Markdown is allowed and you can edit this later in the UI. WANDB_PROJECT The project associated with your run. This can also be set with wandb init , but the environmental variable will override the value. WANDB_RESUME By default this is set to never . If set to auto wandb will automatically resume failed runs. If set to must forces the run to exist on startup. If you want to always generate your own unique ids, set this to allow and always set WANDB_RUN_ID . WANDB_RUN_GROUP Specify the experiment name to automatically group runs together. See grouping for more info. WANDB_RUN_ID Set this to a globally unique string (per project) corresponding to a single run of your script. It must be no longer than 64 characters. All non-word characters will be converted to dashes. This can be used to resume an existing run in cases of failure. WANDB_QUIET Set this to true to limit statements logged to standard output to critical statements only. If this is set all logs will be written to $WANDB_DIR/debug.log . WANDB_SILENT Set this to true to silence wandb log statements. This is useful for scripted commands. If this is set all logs will be written to $WANDB_DIR/debug.log . WANDB_SHOW_RUN Set this to true to automatically open a browser with the run url if your operating system supports it. WANDB_SWEEP_ID Add sweep ID tracking to Run objects and related classes, and display in the UI. WANDB_TAGS A comma separated list of tags to be applied to the run. WANDB_USERNAME The username of a member of your team associated with the run. This can be used along with a service account API key to enable attribution of automated runs to members of your team. WANDB_USER_EMAIL The email of a member of your team associated with the run. This can be used along with a service account API key to enable attribution of automated runs to members of your team. If you’re running containers in Singularity you can pass environment variables by pre-pending the above variables with SINGULARITYENV_ . More details about Singularity environment variables can be found here . If you’re running batch jobs in AWS, it’s easy to authenticate your machines with your Forge credentials. Create an API key at User Settings , and set the WANDB_API_KEY environment variable in the AWS batch job spec .