ICC Demo Workspace

Recordings, curated datasets, and training workflows for the WavesFM ICC presentation.

Workflow

1. Upload recordings — drop .sigmf-data + .sigmf-meta pairs. Git LFS tracks them automatically via .gitattributes.
2. Curate — open the Curator UI, select recordings from this repo, configure slicer + qualifier, produce an HDF5 dataset.
3. Commit dataset — use the Curator's "Commit to Repository" button to land the curated .h5 back here.
4. Train — open the Model Trainer, select this repo + WavesFM Linear Probe (or LoRA), pick the dataset, submit the run.
5. Watch action_run — the trainer renders .riahub/workflows/train.yaml and triggers a runner job. Progress lives under the Actions tab.

Notes

• WavesFM foundation model: qoherent/wavesfm-base/wavesfm-v1p0.pth — injected into the workflow automatically.
• If you upload a binary format not in .gitattributes, add it BEFORE the first commit of that file (LFS can't retroactively un-track).