Train models with self-supervised learning in a single command
Project description
LightlyTrain
Train models with self-supervised learning in a single command
Why LightlyTrain
LightlyTrain uses self-supervised learning (SSL) to train models on large datasets without the need for labels. It provides simple Python, Command Line, and Docker interfaces to train models with popular SSL methods such as SimCLR or DINO. The trained models are ideal starting points for fine-tuning on downstream tasks such as image classification, object detection, and segmentation or for generating image embeddings. Models trained with LightlyTrain result in improved performance, faster convergence, and better generalization compared to models trained without SSL. Image embeddings created with LightlyTrain capture more relevant information than their supervised counterparts and seamlessly extend to new classes due to the unsupervised nature of SSL.
Lightly is the expert in SSL for computer vision and developed LightlyTrain to simplify model training for any task and dataset.
Features
- Train models on any image data without labels
- Train models from popular libraries such as torchvision, TIMM, Ultralytics, and SuperGradients
- Train custom models
- No SSL expertise required
- Automatic SSL method selection (soon!)
- Python, Command Line, and Docker support
- Multi-GPU and multi-node (soon!) support
- Export models for fine-tuning or inference
- Generate and export image embeddings
- Monitor training progress with TensorBoard, Weights & Biases, Neptune, etc. (soon!)
License
LightlyTrain is available under an AGPL-3.0 and a commercial license. Please contact us at info@lightly.ai for more information.
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