flash-attention-windows-wheel

Maintained By
lldacing

Flash Attention Windows Wheel

PropertyValue
LicenseBSD-3-Clause
Authorlldacing

What is flash-attention-windows-wheel?

Flash-attention-windows-wheel is a specialized distribution package that brings the efficient Flash Attention implementation to Windows environments. It provides pre-built wheels for the popular flash-attention library, making it easier for Windows users to integrate this optimization into their deep learning projects.

Implementation Details

The package includes comprehensive build tools and instructions for creating CUDA-enabled wheels on Windows systems. It supports various CUDA versions and can be built with MSVC using the Native Tools Command Prompt for Visual Studio.

  • Supports tag-based versioning (e.g., v2.7.0.post2)
  • Includes parallel building capabilities (configurable worker count)
  • Compatible with CXX11 ABI through build options
  • Requires appropriate CUDA-enabled PyTorch installation

Core Capabilities

  • Windows-native wheel building for flash-attention
  • CUDA acceleration support
  • Configurable build parameters
  • Visual Studio integration
  • Parallel compilation support

Frequently Asked Questions

Q: What makes this model unique?

This distribution uniquely bridges the gap between Windows developers and the flash-attention library, providing native Windows support for a typically Linux-centric tool.

Q: What are the recommended use cases?

This package is ideal for Windows-based machine learning developers who need to implement efficient attention mechanisms in their deep learning models, particularly those working with transformer architectures.

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