A compact, fully open language model that prioritizes transparency over raw capability. At 1.2B parameters with a 2048-token context window, it handles straightforward text tasks but will struggle with complex reasoning or long documents. Its real distinction is that training data, code, and weights are all publicly released, making it a go-to for researchers who want to study model internals rather than just use the output.