README.md

metadata

license: other
tags:
  - wheels
  - cuda
  - pytorch
  - windows
  - linux

image-server-wheels

Prebuilt Python 3.11 wheels.

Contents

File	OS	CUDA	Torch	Source	Notes
ace_step-1.6.0-py3-none-any.whl	any	—	—	built by us	Pure-Python, cross-platform
qwen_tts-0.1.1+deapi3-py3-none-any.whl	any	—	—	built by us	Pure-Python, patched fork (+deapi3)
image_server_kernels-0.3.0-cp311-cp311-win_amd64.whl	Windows x64	12.8	2.8	built by us	FP8 dense + grouped GEMM, NVFP4 W4A4, INT8 W8A8 + ConvRot, fused QK-norm+RoPE. SM89 + SM120
block_sparse_attn-0.0.2-cp311-cp311-win_amd64.whl	Windows x64	12.8	2.8	built by us	Used by video pipeline
block_sparse_attn-0.0.2-cp311-cp311-linux_x86_64.whl	Linux x86_64	12.8	2.8	built by us	Used by video pipeline
q8_kernels-0.0.5-cp311-cp311-win_amd64.whl	Windows x64	12.8	2.8	built by us	Used by LTX video
q8_kernels-0.0.5-cp311-cp311-linux_x86_64.whl	Linux x86_64	12.8	2.8	built by us	Used by LTX video
sageattention-2.2.0+cu128torch2.8.0-cp311-cp311-win_amd64.whl	Windows x64	12.8	2.8	woct0rdho/SageAttention	Mirror of upstream release
flash_attn-2.8.2+cu128torch2.8-cp311-cp311-win_amd64.whl	Windows x64	12.8	2.8	mjun0812/flash-attention-prebuild-wheels	Mirror of upstream release
flash_attn-2.8.3+cu130torch2.10-cp311-cp311-win_amd64.whl	Windows x64	13.0	2.10	mjun0812/flash-attention-prebuild-wheels	Mirror of upstream release
flash_attn-2.8.3+cu128torch2.8-cp311-cp311-linux_x86_64.whl	Linux x86_64	12.8	2.8	mjun0812/flash-attention-prebuild-wheels	Mirror of upstream release

Direct install

BASE=https://huggingface.co/deAPI-ai/image-server-wheels/resolve/main

# Windows
pip install $BASE/image_server_kernels-0.3.0-cp311-cp311-win_amd64.whl
pip install $BASE/q8_kernels-0.0.5-cp311-cp311-win_amd64.whl
pip install $BASE/block_sparse_attn-0.0.2-cp311-cp311-win_amd64.whl
pip install $BASE/flash_attn-2.8.2+cu128torch2.8-cp311-cp311-win_amd64.whl
pip install $BASE/sageattention-2.2.0+cu128torch2.8.0-cp311-cp311-win_amd64.whl
pip install --no-deps $BASE/ace_step-1.6.0-py3-none-any.whl
pip install --no-deps $BASE/qwen_tts-0.1.1+deapi3-py3-none-any.whl

# Linux
pip install $BASE/q8_kernels-0.0.5-cp311-cp311-linux_x86_64.whl
pip install $BASE/block_sparse_attn-0.0.2-cp311-cp311-linux_x86_64.whl
pip install --no-deps $BASE/flash_attn-2.8.3+cu128torch2.8-cp311-cp311-linux_x86_64.whl

sageattention is required by the MiniMax-H3 video model, which imports it unconditionally. Every other model that can use it falls back to SDPA when it is absent, so on a box that does not serve H3 the wheel is optional.

Wheels are Windows-only unless a linux_x86_64 row exists above. There is currently no Linux build of image_server_kernels or sageattention here.

Credits

flash_attn wheels are mirrored from mjun0812/flash-attention-prebuild-wheels — all credit for those builds goes to the upstream author.

sageattention is a mirror, not our build. The library is thu-ml/SageAttention (Apache-2.0); the Windows wheel is built and published by woct0rdho, and we found it through wildminder/AI-windows-whl, which indexes Windows CUDA wheels. All credit for the library and the build goes to them. The file here is byte-identical to the upstream release (sha256:4379951403809dfcd5b1e10d35e287abf42afafb7b27615c09d6062cfbdf230a).

We mirror third-party wheels so the install scripts have a single source of truth and do not break if upstream release URLs change.

The remaining wheels (ace_step, qwen_tts, image_server_kernels, block_sparse_attn, q8_kernels) were built in-house.