Summary
The user is moving from fine-tuning dense 3B/7B models to NVIDIA's Nemotron 3 Nano, a 30B-A3B hybrid Mamba-Attention-MoE architecture, for multi-task reasoning. This new architecture better suits their training goals, but the user lacks experience fine-tuning such hybrid models. The core challenge is understanding how fine-tuning strategies differ when transitioning from traditional dense transformers to this novel Mamba+MoE architecture.
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