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# RIA Hub Technical Demo
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This repository demonstrates a full ML pipeline via Gitea Actions:
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- **Recordings**
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A collection of raw `.npy` radio recordings stored via Git LFS.
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- **Workflows**
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A CI pipeline that automatically:
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1. Builds a labeled dataset from raw recordings
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2. Trains a model on that dataset
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3. Optimizes the model and packages an inference application
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- **Scripts**
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- `scripts/build_dataset.sh`
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Reads through `recordings/`, applies preprocessing, and outputs training `.npz` or `.csv` files into `data/`.
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- `scripts/train_model.sh`
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Consumes `data/`, trains a PyTorch model, and writes checkpoints to `checkpoints/`.
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- `scripts/build_app.sh`
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Takes the best checkpoint and builds a small inference CLI or server in `dist/`.
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