timm
  • 🌍GET STARTED
    • Home
    • Quickstart
    • Installation
  • 🌍TUTORIALS
    • Using Pretrained Models as Feature Extractors
    • Training With The Official Training Script
    • Share and Load Models from the BOINC AI Hub
  • 🌍MODEL PAGES
    • Model Summaries
    • Results
    • Adversarial Inception v3
    • AdvProp (EfficientNet)
    • Big Transfer (BiT)
    • CSP-DarkNet
    • CSP-ResNet
    • CSP-ResNeXt
    • DenseNet
    • Deep Layer Aggregation
    • Dual Path NetwORK(DPN)
    • ECA-ResNet
    • EfficientNet
    • EfficientNet (Knapsack Pruned)
    • Ensemble Adversarial Inception ResNet v2
    • ESE-VoVNet
    • FBNet
    • (Gluon) Inception v3
    • (Gluon) ResNet
    • (Gluon) ResNeXt
    • (Gluon) SENet
    • (Gluon) SE-ResNeXt
    • (Gluon) Xception
    • HRNet
    • Instagram ResNeXt WSL
    • Inception ResNet v2
    • Inception v3
    • Inception v4
    • (Legacy) SE-ResNet
    • (Legacy) SE-ResNeXt
    • (Legacy) SENet
    • MixNet
    • MnasNet
    • MobileNet v2
    • MobileNet v3
    • NASNet
    • Noisy Student (EfficientNet)
    • PNASNet
    • RegNetX
    • RegNetY
    • Res2Net
    • Res2NeXt
    • ResNeSt
    • ResNet
    • ResNet-D
    • ResNeXt
    • RexNet
    • SE-ResNet
    • SelecSLS
    • SE-ResNeXt
    • SK-ResNet
    • SK-ResNeXt
    • SPNASNet
    • SSL ResNet
    • SWSL ResNet
    • SWSL ResNeXt
    • (Tensorflow) EfficientNet
    • (Tensorflow) EfficientNet CondConv
    • (Tensorflow) EfficientNet Lite
    • (Tensorflow) MobileNet v3
    • (Tensorflow) MixNet
    • (Tensorflow) MobileNet v3
    • TResNet
    • Wide ResNet
    • Xception
  • 🌍REFERENCE
    • Models
    • Data
    • Optimizers
    • Learning Rate Schedulers
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Last updated 1 year ago

timm is a library containing SOTA computer vision models, layers, utilities, optimizers, schedulers, data-loaders, augmentations, and training/evaluation scripts.

It comes packaged with >700 pretrained models, and is designed to be flexible and easy to use.

Read the to get up and running with the timm library. You will learn how to load, discover, and use pretrained models included in the library.

Tutorials

Learn the basics and become familiar with timm. Start here if you are using timm for the first time!

Technical descriptions of how timm classes and methods work.

🌍
quick start guide
Reference