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For those running machine learning experiments in the Julia programming language, a community contributor has created an unofficial set of Julia bindings called wandb.jl that you can use. You can find examples in the documentation on the wandb.jl repository. Their “Getting Started” example is here: 
using Wandb, Dates, Logging

# Start a new run, tracking hyperparameters in config
lg = WandbLogger(project = "Wandb.jl",
                 name = "wandbjl-demo-$(now())",
                 config = Dict("learning_rate" => 0.01,
                               "dropout" => 0.2,
                               "architecture" => "CNN",
                               "dataset" => "CIFAR-100"))

# Use LoggingExtras.jl to log to multiple loggers together
global_logger(lg)

# Simulating the training or evaluation loop
for x ∈ 1:50
    acc = log(1 + x + rand() * get_config(lg, "learning_rate") + rand() + get_config(lg, "dropout"))
    loss = 10 - log(1 + x + rand() + x * get_config(lg, "learning_rate") + rand() + get_config(lg, "dropout"))
    # Log metrics from your script to W&B
    @info "metrics" accuracy=acc loss=loss
end

# Finish the run
close(lg)