claude

Zaraat Dost · ML

Segmentation training conventions, pre-flight bug checks, Colab patterns, model cards

10 on GitHubby Zaraat Dost ML/GIS teamv7.6.1MITupdated 1 month agogeospatial
/

Plugin zd-ml from marketplace zaraatdost in Adilmunawar/ZD-claude-plugin. Commands read from the repo's manifest — 1 month ago.

What it installs

Skills (4)

  • colab-ram-safe

    Patterns for RAM-limited notebooks: windowed reads, patch shards, progress files, Drive checkpoints.

  • model-card

    Write an HF-compatible model card (data, classes, metrics, limits) next to a checkpoint.

  • seg-preflight

    Ten-point checklist that catches common segmentation-pipeline bugs (checkpoint keys, shared dataset refs, split leakage, nodata, class balance). Apply before any training run or when predictions are garbage.

  • train-template

    Structure for a PyTorch segmentation training script: resume, early stopping, cosine LR, AMP, full-state checkpoints, tiled inference.

Subagents (1)

  • seg-trainer

    Trains, fine-tunes and evaluates satellite segmentation models (UNet/HRNet/SegFormer, PyTorch, smp, timm, HF) with pre-flight checks, resumable checkpoints and model cards.

View source on GitHub

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