Fine-Tuning problems
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- Dominant language
- Python
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Description
Thank you for your excellent work on the Aurora model — it's been incredibly promising for high-resolution global weather forecasting.
I’m currently attempting to fine-tune Aurora on a custom ERA5 dataset (e.g., adding new surface variables like 2m dewpoint and specific pressure levels such as 950 hPa). While I have gone through the available documentation and supplementary materials, I’m still unclear on the full recommended procedure for implementing fine-tuning in practice.
Could you please provide:
A complete, minimal working example (preferably Python script) for fine-tuning Aurora using a local dataset;
Any official script or reference implementation used for fine-tuning in the paper or experiments.
If such an example already exists, I’d appreciate a link or guidance on where to find it.Thanks again for your help and for open-sourcing such an impactful model!
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Review the available documentation and supplementary materials first, then locate any existing fine-tuning scripts or reference implementations for Aurora. Done means providing a complete minimal Python example for fine-tuning with a local ERA5 dataset, or linking to an official example if one already exists.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Documentation
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100