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LightlyTrain documentation
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0.6.3 ▼
  • Quick Start
  • Installation
  • Train
  • Export
  • Embed
  • Models
    • Torchvision
    • TIMM
    • Ultralytics
    • RT-DETR
    • RF-DETR
    • YOLOv12
    • SuperGradients
    • Custom Models
  • Methods
    • Distillation (recommended 🚀)
    • DINO
    • SimCLR
    • Configuring Image Augmentations
  • Performance
    • Multi-GPU
    • Multi-Node
    • Hardware Recommendations
  • Docker
  • Tutorials
    • Classification with Torchvision’s ResNet
    • Object Detection with Ultralytics’ YOLO
    • Monocular Depth Estimation with fastai U-Net (Advanced)
    • Google Colab Notebooks
  • Python API
    • lightly_train
  • FAQ
  • Changelog
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Tutorials¶

In the following, some tutorials using LightlyTrain can be found. The tutorials are a good starting point to learn about LightlyTrain.

  • Classification with Torchvision’s ResNet
  • Object Detection with Ultralytics’ YOLO
  • Monocular Depth Estimation with fastai U-Net (Advanced)

We’ve also prepared some Google Colab notebooks for some packages we support. You can find them in the following page:

  • Google Colab Notebooks
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Classification with Torchvision’s ResNet
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