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Systematic study of LoRA fine-tuning strategies for IBM Granite 4.0-H-Micro (Mamba-2 + Transformer hybrid). Demonstrates the impact of architecture-aware target selection and SSM core parameter co-training, including analysis of PEFT serialization behavior. Reports up to 37% relative improvement over LoRA-only baselines.

  • Updated Mar 1, 2026
  • Python

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