Get involved

The lab is small and the work is public, so the most useful help is concrete: data, failure cases, and things built on the models. Questions, corrections and collaboration are all welcome.

Ways to help

  • Contribute data

    Annotated Khmer text, scanned documents, or transcriptions are the scarcest resource in this whole space. Even small, well-labelled sets are useful.

  • Report where models fail

    Real documents that the models get wrong are worth more than another benchmark. Failure cases directly shape the next training run.

  • Build on the work

    Build something on top of the models and say what broke. Nothing surfaces gaps faster than someone trying to ship with them.

Where to find us

GitHub
github.com/netra-ai-lab
Source code for every project. Fork it, send a pull request, or read how the models were trained.
Issues
Report something
Bugs, model failures, and questions about training details or usage. The fastest way to get a reply.
Hugging Face
huggingface.co/Netra-Lab
Model weights, datasets, and hosted demos you can try in the browser without installing anything.
Email
darayutnhem009@gmail.com
For collaboration, research partnerships, or anything that doesn't belong in a public thread.