model-size-reduction

What problem does it solve?

Model size reduction solves the problem of deploying or sharing oversized Hugging Face checkpoints when tooling like mergekit cannot handle the architecture or when you need a smaller, more portable artifact.

Core Features & Use Cases

• Architecture-agnostic slimming: Recasts dtype, drops transformer blocks via state_dict key surgery, extracts LoRA from finetuned-minus-base, and performs delta sparsification using DARE/TIES/DELLA.
• Checkpointed multi-stage pipelines: Runs reduction as a resumable series of full model directories so interrupted jobs can continue.
• Validation guardrails: Measures reduction aggressiveness with perplexity (relative delta) and provides failure boundaries like unrecognized layer-key patterns or missing safetensors.

Quick Start

Use this skill to reduce a Hugging Face checkpoint by first sparsifying the fine-tune delta (DARE/TIES/DELLA), then optionally dropping layers, casting to fp16 or bf16, and finally validating perplexity before publishing.