Skip to main content
Start logging your first experiment in 4 steps:
  1. Create an account/organization at https://trakkur.trainy.ai
  2. Install the Python SDK. In your Python environment, install the latest build 
    pip install "trainy-mlop[nightly]"
  3. Request an API key through the terminal via: 
    import mlop
mlop.login()
  4. Log your first experiment! 
    # hello_mlop.py
import mlop
 
config = {'lr': 0.001, 'epochs': 1000}
run = mlop.init(project="mlop", name="experiment", config=config)
 
# insert custom model training code
for i in range(config['epochs']):
    run.log({"val/loss": 0})
 
run.finish()
The code will print out a url where you can view your current run. The web dashboard allows you to compare time series between runs. The output for the above script might be the following. 
(mlop) ubuntu@ip-111-111-111-111:~$ python hello_mlop.py 
mlop: 🚀 19:52:01 | Authentication: logged in as trainy
mlop: 🚀 19:52:01 | Interface: find live updates at https://trakkur.trainy.ai/o/myorg/projects/my-project/mzHx3
mlop: 🚀 19:52:06 | Interface: find 1001 synced entries at https://trakkur.trainy.ai/o/myorg/projects/my-project/mzHx3