# Welcome to AutoTransformers
**Transform data into high-performance machine learning models using only a few lines of code. No machine-learning expertise required.**

<img src="/_static/img/idea.png" style="width: 40% !important;" />

The {term}`AutoTransformers library` automatically transforms data into ML {term}`models<Model>` that can, later on, be used to predict new data and automate tasks such as text classification, document information extraction etc. The {term}`AutoTransformers library` not only supports many different {term}`domains<Domain>` such as text, documents or images but creates models also with very high performance using only little amount of training data. Our research department ensures that the {term}`AutoTransformers library` provides the highest performance by implementing and testing cutting-edge technologies and research using our internal DeepOpinion Benchmarks that include over 40 real-world datasets. Additionally, only a few lines of code are needed to use the {term}`AutoTransformers library` and training as well as predicting new data can be executed completely on-premise such that your data is never shared with any 3rd party provider.

```{note}
   The {term}`AutoTransformers library` is also the backbone of our no-code ML solution DeepOpinion Studio (https://studio.deepopinion.ai/) which can be used to create high-performance models without writing a single line of code.
```

## Key Features
Here we list some of the core features of the {term}`AutoTransformers library`:
- Automatically creates high {term}`performance<Performance>` machine learning models
- The `at wizard` generates the training script, prediction script as well as the dataset template and a README for you to reduce the development time further
- High performance also with little labeling effort through features such as {term}`Active learning`
- One API for many {term}`domains<Domain>` such as text, documents or images
- No ML expertise and only a few lines of code are required
- 100\% on-premise execution
- Supports parallel {term}`task<Task>` prediction (e.g. classification + information extraction) depending on your data and your requirements.
- Open ecosystem and 3rd party integrations (e.g. [WandB](https://wandb.ai/), [ClearML](https://clear.ml/))
- Optionally integrates [Deepspeed](https://www.deepspeed.ai/) for {term}`LLM` training.
- Out-of-the-box distributed execution on multiple GPUs
- Automatic checkpointing to stop and continue training at any time.
- Fully flexible configuration for high customizability, custom implementations etc.

```{eval-rst}
.. toctree::
   :maxdepth: 2
   :caption: Getting Started

   getting_started/system_comparison
   getting_started/system_requirements
   getting_started/install
   getting_started/getting_started_wizard
   getting_started/getting_started_manual
   getting_started/data
   getting_started/babysit_training
   getting_started/env_variables
   getting_started/document
   getting_started/computer_vision

.. toctree::
   :maxdepth: 1
   :caption: News

   changelog


.. toctree::
   :maxdepth: 1
   :caption: Tutorials

   examples/01_getting_started
   examples/02_text_multi_classification
   examples/03_text_multisingle_classification
   examples/04_document_information_extraction
   examples/05_multitask
   examples/06_config
   examples/07_save_and_load
   examples/08_tracking
   examples/09_active_learning
   examples/10_markup_text_information_extraction
   examples/11_document_classification


.. toctree::
   :maxdepth: 1
   :caption: Developer API

   api/api


.. toctree::
   :maxdepth: 1
   :caption: Resources

   shared/glossary
   resources/about


Indices and tables
==================
* :ref:`genindex`
* :ref:`modindex`
* :ref:`search`
```