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ColossalAI

hpcaitech/ColossalAI

Making large AI models cheaper, faster and more accessible

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Python Apache-2.0Created Oct 28, 2021

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Overview

ColossalAI is a Python library that aims to reduce the cost and increase the speed of developing large-scale AI models through advanced parallelism techniques like data-parallelism, model-parallelism, and pipeline-parallelism.

Capability facts

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python

Source: github.language · Jul 11, 2026

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Compatibility

Sourced claims from the README excerpt - not unsourced marketing copy.

Python runtimePython

Source: README excerpt (regex_v1, Jul 11, 2026)

- Python >= 3.7
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README

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Installation

Requirements:

If you encounter any problem with installation, you may want to raise an issue in this repository.


Install from PyPI

You can easily install Colossal-AI with the following command. By default, we do not build PyTorch extensions during installation.

pip install colossalai

Note: only Linux is supported for now.

However, if you want to build the PyTorch extensions during installation, you can set BUILD_EXT=1.

BUILD_EXT=1 pip install colossalai

Otherwise, CUDA kernels will be built during runtime when you actually need them.

We also keep releasing the nightly version to PyPI every week. This allows you to access the unreleased features and bug fixes in the main branch. Installation can be made via

pip install colossalai-nightly

install colossalai

pip install .


By default, we do not compile CUDA/C++ kernels. ColossalAI will build them during runtime.
If you want to install and enable CUDA kernel fusion (compulsory installation when using fused optimizer):

```shell
BUILD_EXT=1 pip install .

For Users with CUDA 10.2, you can still build ColossalAI from source. However, you need to manually download the cub library and copy it to the corresponding directory.


---

# install
BUILD_EXT=1 pip install .

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