Adapter Composition And Inference With Merged Weight Strategies

via “adapter merging and unmerging”

Parameter-efficient fine-tuning — LoRA, QLoRA, adapter methods for LLMs on consumer GPUs.

Unique: Implements reversible weight merging by storing the original base weights separately and computing merged_weight = base_weight + adapter_weight, enabling unmerge_adapter() to restore the original state. The merge operation is mathematically simple but requires careful state management to support unmerging.

vs others: Eliminates adapter inference overhead (5-10% latency reduction) and removes PEFT runtime dependency, enabling deployment as standard transformers models, but at the cost of losing adapter modularity and storage efficiency.