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flash-attention-prebuild-wh…/README.md
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2025-05-18 02:26:18 +09:00

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# flash-attention pre-build wheels
This repository provides wheels for the pre-built [flash-attention](https://github.com/Dao-AILab/flash-attention).
Since building flash-attention takes a **very long time** and is resource-intensive,
I also build and provide combinations of CUDA and PyTorch that are not officially distributed.
The building Github Actions Workflow can be found [here](./.github/workflows/build.yml).
The built packages are available on the [release page](https://github.com/mjun0812/flash-attention-prebuild-wheels/releases).
## Install
1. Select the versions for Python, CUDA, PyTorch, and flash_attn.
```bash
flash_attn-[flash_attn Version]+cu[CUDA Version]torch[PyTorch Version]-cp[Python Version]-cp[Python Version]-linux_x86_64.whl
# Example: Python 3.11, CUDA 12.4, PyTorch 2.5, and flash_attn 2.6.3
flash_attn-2.6.3+cu124torch2.5-cp312-cp312-linux_x86_64.whl
```
2. Find the corresponding version of a wheel from the below table and [releases](https://github.com/mjun0812/flash-attention-prebuild-wheels/releases)
3. Direct Install or Download and Local Install
```bash
# Direct Install
pip install https://github.com/mjun0812/flash-attention-prebuild-wheels/releases/download/v0.0.0/flash_attn-2.6.3+cu124torch2.5-cp312-cp312-linux_x86_64.whl
# Download and Local Install
wget https://github.com/mjun0812/flash-attention-prebuild-wheels/releases/download/v0.0.0/flash_attn-2.6.3+cu124torch2.5-cp312-cp312-linux_x86_64.whl
pip install ./flash_attn-2.6.3+cu124torch2.5-cp312-cp312-linux_x86_64.whl
```
## Packages
### v0.0.9
[Release](https://github.com/mjun0812/flash-attention-prebuild-wheels/releases/tag/v0.0.9)
| Flash-Attention | Python | PyTorch | CUDA |
| ------------------- | ---------------- | ------- | ------ |
| 2.4.3, 2.5.9, 2.6.3 | 3.10, 3.11, 3.12 | 2.7.0 | 12.8.1 |
### v0.0.8
[Release](https://github.com/mjun0812/flash-attention-prebuild-wheels/releases/tag/v0.0.8)
| Flash-Attention | Python | PyTorch | CUDA |
| -------------------------------- | ---------------- | -------------------------- | ---------------------- |
| 2.4.3, 2.5.9, 2.6.3, 2.7.4.post1 | 3.10, 3.11, 3.12 | 2.4.1, 2.5.1, 2.6.0, 2.7.0 | 11.8.0, 12.4.1, 12.6.3 |
### v0.0.7
Skip for experimental reasons.
### v0.0.6
[Release](https://github.com/mjun0812/flash-attention-prebuild-wheels/releases/tag/v0.0.6)
| Flash-Attention | Python | PyTorch | CUDA |
| -------------------------------- | ---------------- | --------------------------------- | -------------- |
| 2.4.3, 2.5.9, 2.6.3, 2.7.4.post1 | 3.10, 3.11, 3.12 | 2.2.2, 2.3.1, 2.4.1, 2.5.1, 2.6.0 | 12.4.1, 12.6.3 |
### v0.0.5
[Release](https://github.com/mjun0812/flash-attention-prebuild-wheels/releases/tag/v0.0.5)
| Flash-Attention | Python | PyTorch | CUDA |
| ------------------ | ---------------- | ----------------------------------------------- | -------------- |
| 2.6.3, 2.7.4.post1 | 3.10, 3.11, 3.12 | 2.0.1, 2.1.2, 2.2.2, 2.3.1, 2.4.1, 2.5.1, 2.6.0 | 12.4.1, 12.6.3 |
### v0.0.4
[Release](https://github.com/mjun0812/flash-attention-prebuild-wheels/releases/tag/v0.0.4)
| Flash-Attention | Python | PyTorch | CUDA |
| --------------- | ---------------- | ---------------------------------------- | ---------------------- |
| 2.7.3 | 3.10, 3.11, 3.12 | 2.0.1, 2.1.2, 2.2.2, 2.3.1, 2.4.1, 2.5.1 | 11.8.0, 12.1.1, 12.4.1 |
### v0.0.3
[Release](https://github.com/mjun0812/flash-attention-prebuild-wheels/releases/tag/v0.0.3)
| Flash-Attention | Python | PyTorch | CUDA |
| --------------- | ---------------- | ---------------------------------------- | ---------------------- |
| 2.7.2.post1 | 3.10, 3.11, 3.12 | 2.0.1, 2.1.2, 2.2.2, 2.3.1, 2.4.1, 2.5.1 | 11.8.0, 12.1.1, 12.4.1 |
### v0.0.2
[Release](https://github.com/mjun0812/flash-attention-prebuild-wheels/releases/tag/v0.0.2)
| Flash-Attention | Python | PyTorch | CUDA |
| -------------------------------- | ---------------- | ---------------------------------------- | ---------------------- |
| 2.4.3, 2.5.6, 2.6.3, 2.7.0.post2 | 3.10, 3.11, 3.12 | 2.0.1, 2.1.2, 2.2.2, 2.3.1, 2.4.1, 2.5.1 | 11.8.0, 12.1.1, 12.4.1 |
### v0.0.1
[Release](https://github.com/mjun0812/flash-attention-prebuild-wheels/releases/tag/v0.0.1)
| flash-attention | Python | PyTorch | CUDA |
| --------------------------------- | ---------------- | ---------------------------------------- | ---------------------- |
| 1.0.9, 2.4.3, 2.5.6, 2.5.9, 2.6.3 | 3.10, 3.11, 3.12 | 2.0.1, 2.1.2, 2.2.2, 2.3.1, 2.4.1, 2.5.0 | 11.8.0, 12.1.1, 12.4.1 |
### v0.0.0
[Release](https://github.com/mjun0812/flash-attention-prebuild-wheels/releases/tag/v0.0.0)
| flash-attention | Python | PyTorch | CUDA |
| -------------------------- | ---------- | ---------------------------------------- | ---------------------- |
| 2.4.3, 2.5.6, 2.5.9, 2.6.3 | 3.11, 3.12 | 2.0.1, 2.1.2, 2.2.2, 2.3.1, 2.4.1, 2.5.0 | 11.8.0, 12.1.1, 12.4.1 |
## Self build
If you want to build the wheels yourself, you can folk this repository and run the build workflow.
1. Fork this repository
2. Edit workflow file `.github/workflows/build.yml` to set the version you want to build.
3. Add tag `v*.*.*` to trigger the build workflow.
### Self-Hosted Runner Build
In some version combinations, you cannot build wheels on GitHub-hosted runners due to job time limitations.
To build the wheels for these versions, you can use self-hosted runners.
```bash
git clone https://github.com/mjun0812/flash-attention-prebuild-wheels.git
cd self-hosted-runner
cp env.template env
```
Edit `env` file to set the environment variables.
```bash
# Edit env
PERSONAL_ACCESS_TOKEN=[Github Personal Access Token]
```
Edit compose.yml file if you use repository folked from this repository.
```yaml
services:
runner:
privileged: true
build:
context: .
dockerfile: Dockerfile
args:
REPOSITORY_URL: [Target Repository URL]
PERSONAL_ACCESS_TOKEN: $PERSONAL_ACCESS_TOKEN
GH_RUNNER_VERSION: 2.324.0
RUNNER_NAME: self-hosted-runner
RUNNER_GROUP: default
RUNNER_LABELS: self-hosted
TARGET_ARCH: x64
```
Then, build and run the docker container.
```bash
# Build and run
docker compose build
docker compose up -d
```
## Original Repository
[repo](https://github.com/Dao-AILab/flash-attention)
```bibtex
@inproceedings{dao2022flashattention,
title={Flash{A}ttention: Fast and Memory-Efficient Exact Attention with {IO}-Awareness},
author={Dao, Tri and Fu, Daniel Y. and Ermon, Stefano and Rudra, Atri and R{\'e}, Christopher},
booktitle={Advances in Neural Information Processing Systems (NeurIPS)},
year={2022}
}
@inproceedings{dao2023flashattention2,
title={Flash{A}ttention-2: Faster Attention with Better Parallelism and Work Partitioning},
author={Dao, Tri},
booktitle={International Conference on Learning Representations (ICLR)},
year={2024}
}
```