StijnVerdenius/SNIP-it
This repository is the official implementation of the paper Pruning via Iterative Ranking of Sensitivity Statistics and implements novel pruning / compression algorithms for deep learning / neural networks. Amongst others it implements structured pruning before training, its actual parameter shrinking and unstructured before/during training.
No commits in the last 6 months.
Stars
32
Forks
4
Language
Python
License
MIT
Category
Last pushed
May 22, 2023
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/StijnVerdenius/SNIP-it"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
Xilinx/brevitas
Brevitas: neural network quantization in PyTorch
open-mmlab/mmengine
OpenMMLab Foundational Library for Training Deep Learning Models
fastmachinelearning/qonnx
QONNX: Arbitrary-Precision Quantized Neural Networks in ONNX
google/qkeras
QKeras: a quantization deep learning library for Tensorflow Keras
tensorflow/model-optimization
A toolkit to optimize ML models for deployment for Keras and TensorFlow, including quantization...