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:
Xorbits
名字本身有许多含义,你可以理解成 X-or-bits(未来或比特)
,也可以理解成 X-orbits(未来的轨道)
,或者 xor-bits(异或比特)
等等,随意按你的想法来理解。
参与项目#
平台 |
目的 |
询问使用的问题,参与开发的讨论 |
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报告 bug 或者发起新特性请求 |
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与其他 Xorbits 用户一起讨论 |
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询问 Xorbits 使用问题 |
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获取最新特性的更新 |