ffcv is a drop-in data loading system that dramatically increases data throughput in model training. From gridding to benchmarking to fast research iteration, there are many reasons to want faster model training. Below we present premade codebases for training on ImageNet and CIFAR, including both (a) extensible codebases and (b) numerous premade training configurations.

Features

  • Train an ImageNet model on one GPU in 35 minutes (98¢/model on AWS)
  • Train a CIFAR-10 model on one GPU in 36 seconds (2¢/model on AWS)
  • Train a $YOUR_DATASET model $REALLY_FAST (for $WAY_LESS)
  • Keep your training algorithm the same, just replace the data loader
  • ffcv also comes prepacked with fast, simple code for standard vision benchmarks
  • Accelerate any learning system with ffcv

Project Samples

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Categories

Machine Learning

License

Apache License V2.0

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Additional Project Details

Operating Systems

Linux, Mac, Windows

Programming Language

Python

Related Categories

Python Machine Learning Software

Registered

2024-08-07