Relational Transformers
=======================

Relational Transformers runs and adapts RT-J over model-ready relational cell
tensors. Applications own data retrieval and feature encoding; this library
owns the model.

.. toctree::
   :maxdepth: 2
   :caption: Documentation

   docs/installation
   docs/testing
   docs/quickstart
   examples/README
   docs/relational_transformer/usage/usage
   docs/relational_transformer/usage/prediction
   docs/relational_transformer/usage/batches
   docs/relational_transformer/usage/backends
   docs/relational_transformer/usage/efficiency
   docs/relational_transformer/usage/ablation
   docs/relational_transformer/usage/custom_models
   docs/relational_transformer/pretrained_models
   docs/relational_transformer/dataset_overview
   docs/relational_transformer/loss_overview
   docs/relational_transformer/training_overview
   docs/relational_transformer/training/overview
   docs/relational_transformer/training/head_tuning
   docs/relational_transformer/training/full_finetuning
   docs/relational_transformer/training/examples
   docs/package_reference/model
   docs/package_reference/batch
   docs/package_reference/datasets
   docs/package_reference/evaluation
   docs/package_reference/losses
   docs/package_reference/training
   docs/package_reference/onnx