Repository associated with paper titled "CLP: Finetuning Vision-Language-Action Models Requires Fewer Layers Than You Think"
[NIPS 2016] Learning Structured Sparsity in Deep Neural Networks
Official Pytorch implementation of "Filter Pruning by Image Channel Reduction in Pre-Trained Convolutional Neural Networks".
Code for the papers: "Efficient Speech Translation through Model Compression and Knowledge Distillation" and "Iterative Layer Pruning for Efficient Translation Inference"
Intelligent layer pruning toolkit for LLMs featuring iterative optimization, self-healing algorithms, and comprehensive benchmarking.
TALE: training-free task-aware layer pruning for improving LLM accuracy and reducing inference cost
Based on yolov3 and channel and layer pruning
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