Welcome to Xorbits!#
Xorbits is an open-source computing framework that makes it easy to scale data science and machine learning workloads — from data loading to preprocessing, tuning, training, and model serving. Xorbits can leverage multi cores or GPUs to accelerate computation on a single machine, or scale out up to thousands of machines to support processing terabytes of data.
Xorbits provides a suite of best-in-class libraries for data scientists and machine learning practitioners. Xorbits provides the capability to scale tasks without the necessity for extensive knowledge of infrastructure.
Xorbits Data: Load and process datasets, from small to large, using the tools you love💜, such as pandas and Numpy.
Xorbits Train: Train your own state-of-the-art models for ML and DL frameworks such as PyTorch, XGBoost, etc.
Xorbits Tune: Finetune your models by running state of the art algorithms such as PEFT.
Xorbits Inference: Scalable serving to deploy state-of-the-art models. Integrate with the most popular deep learning libraries, like PyTorch, ggml, etc.
Xorbits features a familiar Python API that supports a variety of libraries, including pandas, NumPy, scikit-learn, PyTorch, XGBoost, Xarray, etc. With a simple modification of just one line of code, your pandas workflow can be seamlessly scaled using Xorbits:
As for the name of xorbits, it has many meanings, you can treat it as X-or-bits or X-orbits or xor-bits,
just have fun to comprehend it in your own way.
Getting involved#
Platform |
Purpose |
Asking usage questions and discussing development. |
|
Reporting bugs and filing feature requests. |
|
Collaborating with other Xorbits users. |
|
Asking questions about how to use Xorbits. |
|
Staying up-to-date on new features. |