Small models are cheap to run, but expensive to adapt. The hard part is not only fine-tuning. It is the surrounding loop that involves collecting data, diagnosing failures, building evals, avoiding regressions, choosing curricula, and deciding when an update is safe. This new
Small Models Adaptation Challenges Beyond Fine-Tuning
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