Jeff: Lightweight 0.8B Decision Models Trained Locally with 30ms Inference

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A developer has released Jeff, an open-source project featuring small 0.8-billion-parameter decision-focused language models. The models are designed to be compatible with the Jev specification and can be trained on consumer hardware at home. Inference runs at approximately 30 milliseconds, making the models suitable for fast, lightweight decision-making tasks. The project is publicly available on GitHub under the repository firelex/jeff. It has garnered early attention on Hacker News, though community discussion is still limited.

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