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d-pruner

[NAACL Findings 2024] Pruning as a Domain-specific LLM Extractor. Support LLaMA2.

deep-compression-pytorch

PyTorch implementation of 'Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding' by Song Han, Huizi Mao, William J. Dally

flap

[AAAI 2024] Fluctuation-based Adaptive Structured Pruning for Large Language Models

greedy-layer-pruning

Greedy layer pruning for transformer models.

llm-pruner

[NeurIPS 2023] LLM-Pruner: On the Structural Pruning of Large Language Models. Support LLaMA, Llama-2, BLOOM, Vicuna, Baichuan, etc.

llmprune-besa

BESA is a differentiable weight pruning technique for large language models.

mbs

regularization-pruning

[ICLR'21] Neural Pruning via Growing Regularization (PyTorch)

relative-importance-and-activation-pruning

sparse-gpt-finetuning

Code for my ICLR 2024 TinyPapers paper "Prune and Tune: Improving Efficient Pruning Techniques for Massive Language Models"

sparsegpt

Code for the ICML 2023 paper "SparseGPT: Massive Language Models Can Be Accurately Pruned in One-Shot".

torch-pruning

[CVPR 2023] Towards Any Structural Pruning; LLMs / SAM / Diffusion / Transformers / YOLOv8 / CNNs

transformercompression

For releasing code related to compression methods for transformers, accompanying our publications

wanda

A simple and effective LLM pruning approach.