model-pruning

SKILLFlujo de trabajocomunidad
v0.0.0Orchestra-ResearchMITActualizado hace 2 mFuente →

Reduce LLM size and accelerate inference using pruning techniques like Wanda and SparseGPT. Use when compressing models without retraining, achieving 50% sparsity with minimal accuracy loss, or enabling faster inference on hardware accelerators. Covers unstructured pruning, structured pruning, N:M s

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Skill
AutorOrchestra-Research
Versión0.0.0
LicenciaMIT
CategoríaFlujo de trabajo
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Reduce LLM size and accelerate inference using pruning techniques like Wanda and SparseGPT. Use when compressing models without retraining, achieving 50% sparsity with minimal accuracy loss, or enabling faster inference on hardware accelerators. Covers unstructured pruning, structured pruning, N:M sparsity, magnitude pruning, and one-shot methods.

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