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SpikeForge splits into modular toolkit, model hub, and dashboard packages

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SpikeForge, a Python toolkit for building and testing spiking neural networks, has restructured into four separate packages: spikeforge, spikeforge-targets, spikeforge-hub, and spikeforge-dashboard. The project released versions 0.4.0 and 0.5.0 during this cycle, adding a train/test split for event data, quantization updates, and shared logging via capsize-commons. The modular design allows users to install only the components they need, so a researcher experimenting in Python is not required to install the desktop application or web dashboard. The offline-first model hub lets users browse and use a model catalogue without requiring a network connection for every experiment. Source code is available on GitHub, desktop releases are hosted on itch.io, and package links can be found at spikeforge.net.

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