1 Repo
Awesome GitHub RepositoriesModel Pruning Techniques
Methods for reducing the size and complexity of neural networks by removing or consolidating layers.
Distinguishing note: Focuses on structural reduction of the network architecture to decrease latency, distinct from precision-based compression.
Explore 1 awesome GitHub repository matching artificial intelligence & ml · Model Pruning Techniques. Refine with filters or upvote what's useful.
Awesome Model Pruning Techniques GitHub Repositories
Finde die besten Repos mit KI.Wir suchen mit KI nach den am besten passenden Repositories.
- deepspeedai/deepspeed
deepspeedai/DeepSpeed
42,528Auf GitHub ansehenDeepSpeed is a high-performance library designed to scale deep learning model training and inference across massive clusters of GPUs and compute nodes. It provides a comprehensive suite of tools for distributed training, enabling the execution of models that exceed the memory capacity of single devices through advanced parameter partitioning, pipeline-based model parallelism, and memory-efficient state offloading. The framework distinguishes itself through specialized communication-efficient optimizers and hardware-aware acceleration techniques. By utilizing gradient compression, quantization
The framework decreases inference latency by reducing the number of hidden layers in a neural network while maintaining consistent layer width.
Pythonbillion-parameterscompressiondata-parallelism
