We research methods to make language models more composable, understandable, and reliably controllable — so new capabilities can be added, adapted, and shared with predictable effects.
Each capability attaches to the same base model and comes off cleanly, without disturbing the others. This is an illustration, not a live model.
We share our work through open research, collaborations, and tools for the community.
Partner on research, share a dataset, or bring us a problem worth solving.
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