Arcee Supernova Training Pipeline And Model Composition

Arcee AI's SuperNova training account shows how practical constraints can change the way a smaller model learns from a larger one. Running the larger teacher, Meta's Llama-3.1-405B-Instruct, alongside the training of the 70B student model exceeded the team's hardware capacity. Arcee instead calculated and stored the teacher's scores for possible next pieces of text, compressed that information, and used it later to train the smaller model. The pipeline report describes this as a central part of SuperNova's development.

Separating those stages made the training process feasible on the team's hardware. The compression procedure itself was not fully disclosed, so the account explains the engineering approach without providing a complete reproduction recipe.