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-0.4.3+cu128torch2.8-cp311-cp311-win_amd64.whl	Windows x64	12.8	2.8	built by us	Current. FP8 dense + grouped GEMM, NVFP4 W4A4, INT8 W8A8 + ConvRot, W4A8, GGUF, fused QK-norm+RoPE, Sol-Attn. SM89 + SM120
image_server_kernels-0.4.3+cu129torch2.8-cp311-cp311-linux_x86_64.whl	Linux x86_64	12.9	2.8	built by us	Current. Same op set
image_server_kernels-0.4.2+cu128torch2.8-cp311-cp311-win_amd64.whl	Windows x64	12.8	2.8	built by us	Previous build, kept as a rollback
image_server_kernels-0.4.2+cu129torch2.8-cp311-cp311-linux_x86_64.whl	Linux x86_64	12.9	2.8	built by us	Previous build, kept as a rollback
image_server_kernels-0.3.0-cp311-cp311-win_amd64.whl	Windows x64	12.8	2.8	built by us	Legacy. No Sol-Attn, no W4A8, no bundled GGUF kernels
image_server_kernels-0.3.0+cu129torch2.8-cp311-cp311-linux_x86_64.whl	Linux x86_64	12.9	2.8	built by us	Legacy. Same omissions as the Windows 0.3.0
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
sageattention-2.2.0+cu129torch2.8-cp311-cp311-linux_x86_64.whl	Linux x86_64	12.9	2.8	—
causal_conv1d-1.7.0+cu129torch2.8-cp311-cp311-linux_x86_64.whl	Linux x86_64	12.9	2.8	built by us	Fused causal conv1d for Gated DeltaNet models. Built from unmodified upstream v1.7.0 source. No Windows build
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-0.4.3+cu128torch2.8-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/image_server_kernels-0.4.3+cu129torch2.8-cp311-cp311-linux_x86_64.whl
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 $BASE/sageattention-2.2.0+cu129torch2.8-cp311-cp311-linux_x86_64.whl
pip install --no-deps $BASE/causal_conv1d-1.7.0+cu129torch2.8-cp311-cp311-linux_x86_64.whl
pip install --no-deps $BASE/flash_attn-2.8.3+cu128torch2.8-cp311-cp311-linux_x86_64.whl

Wheels are built for Python 3.11 and the CUDA/torch pair named in each filename. Installing one against a different torch build is the first thing to suspect if the import fails.

Credits

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

The Windows sageattention wheel is a mirror, not our build. The library is thu-ml/SageAttention (Apache-2.0); the 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.

The Linux causal_conv1d wheel is built in-house from the unmodified source of Dao-AILab/causal-conv1d v1.7.0 (BSD-3-Clause, copyright the causal-conv1d contributors). Its LICENSE and AUTHORS ship inside the wheel under dist-info/licenses/. All credit for the library goes to its authors.