installml deploy --config my_project.yaml Your my_project.yaml might look like:
installml run test-env --dry-run If you see ✅ Dry run successful , you’re golden. Now for the fun part. Deploy a production‑ready ML environment:
export INSTALLML_API_KEY="your-api-key-here" To make this permanent, add it to your ~/.bashrc or ~/.zshrc . Run the official installer: installml.com setup
✓ OS detected: Linux (Ubuntu 22.04) ✓ CLI installed to /usr/local/bin/installml ✓ Environment check passed Setup complete — ready to deploy! Run a quick test to confirm everything works:
installml version Expected output:
project: fraud-detection python: 3.10 packages: - numpy - pandas - scikit-learn - torch gpu: optional The CLI will stream the setup logs directly to your terminal. Prefer to keep config in your repo? Create a .installml file:
Now go build something great. 🚀
curl -fsSL https://installml.com/setup | bash Or if you prefer wget :
Get Up and Running in Minutes: Your Guide to installml.com Setup installml deploy --config my_project
installml client v1.2.0 Connected to installml.com (region: us-east) Then try pulling a tiny test environment:
So you’ve signed up for — smart move. Now let’s get your environment ready without the usual headaches. Run the official installer: ✓ OS detected: Linux