| Tutorial | Learning Type | Description |
|---|---|---|
| Hello World | Supervised | Train and use an image similarity model to find similar looking MNIST digits |
| Self-Supervised Learning | Unsupervised | Train an image model using the SimSiam based self-supervised contrastive learning. |
| visualization | Supervised | Train an image similarity model on the Stanford Dogs dataset using Evaluation Callbacks and the interactive visualizer |
| Sampler IO Cookbook | Utils | Examples demonstrating how to use the various in memory batch samplers. |
| CLIP finetuning | Supervised | Finetune CLIP on atric-dataset using multiple negatives ranking loss. |
This repository was archived by the owner on Jul 9, 2025. It is now read-only.
examples
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