HzChen20/opd-wheels

Prebuilt wheels for the OPD environment

Mirror of official upstream release artifacts, re-hosted so machines with slow GitHub access can pull them through hf-mirror.com. Nothing is rebuilt or modified — byte-identical to the GitHub release assets.

flash_attn-2.8.3+cu12torch2.9cxx11abiTRUE-cp312-cp312-linux_x86_64.whl

• Upstream: Dao-AILab/flash-attention v2.8.3
• Size: 243 MiB
• sha256: 4e2f9e39313266b1544b68138b15b91ee6221eccf14f7902b7c6620351340810
• License: BSD-3-Clause (upstream)

Matches exactly one environment. All four coordinates have to line up:

Coordinate	Value	Why it is fixed
torch	2.9.0	vllm==0.12.0 pins torch==2.9.0 (hard == in its metadata)
CUDA	cu12	PyPI torch 2.9.0 is a cu128 build (nvidia-*-cu12==12.8.x)
cxx11abi	TRUE	the only variant published for torch2.9
python	cp312	the only variant published for torch2.9 — 3.10/3.11/3.13 do not exist
platform	linux_x86_64	aarch64 exists upstream but is not mirrored here

Requires compute capability >= 8.0 (Ampere or newer). FlashAttention-2 has no kernels for sm70 (V100). Check with nvidia-smi --query-gpu=compute_cap --format=csv before bothering.

Also note it is not needed for vLLM generation at all — verl's flash_attn imports live under verl/models/*/megatron/*, which the generation path never touches. It is only required once FSDP KL training starts.

Install

HF_ENDPOINT=https://hf-mirror.com hf download HzChen20/opd-wheels \
    --repo-type dataset --include "*.whl" --local-dir ./wheels

pip install ./wheels/flash_attn-2.8.3+cu12torch2.9cxx11abiTRUE-cp312-cp312-linux_x86_64.whl
python -c "import flash_attn; print(flash_attn.__version__)"

Verify the transfer first if the link is unreliable:

sha256sum -c <<< "4e2f9e39313266b1544b68138b15b91ee6221eccf14f7902b7c6620351340810  ./wheels/flash_attn-2.8.3+cu12torch2.9cxx11abiTRUE-cp312-cp312-linux_x86_64.whl"