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Description
Add a hello_world_danra.ipynb notebook to docs/notebooks/ providing a step-by-step guide for running a full model training using DANRA data. This improves onboarding and showcases neural-lam's capabilities.
Note: The COSMO equivalent has been split into a separate issue: #587
Stale PR: #202 (thank you @Jayant-kernel!) Current PR: #577 builds on top of #202
Proposed notebook contents
- Install Neural-LAM with all dependencies (PDM + ipykernel)
- Data loading and preprocessing using
tests/datastore_examples/mllam/danra.example.yaml - Model configuration and HiLAM graph generation
- Training on CPU (with
--flags) - Evaluation and visualization using built-in maps and charts + wandb
Additional considerations
- Use a small subset of DANRA data for quick execution
- Include explanations for each step
- Highlight key parameters and their effects
- Provide tips for scaling to larger datasets