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Frank 9bfa0be85d chore(skills): promote runbook skills to managed-skills; drop superseded SKILL.md

- 31 new managed skills (anubis/arr/authentik/hermes/freetoken/podman/llm-swap
  runbooks etc.) now tracked.
- Removed superseded skills: omp_harness_config, peon_ping_integration
  (replaced by user-authored peon-ping-* managed skills),
  rocmfp4-strix-benchmark-orchestration.
- New memory-root skills: niri_compositor_ops, omp_git_workflow,
  omp_model_config, quadlet-media-migration, homelab-service-triage,
  hermes-dankclaw-ops, frank-default-large-ops, caddy-auth-dns-playbook.

2026-09-09 16:20:28 -07:00

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name, description

name	description
freetoken-rocm-build	Verify and execute FreeToken build on ROCm hosts — check gfx1151, ROCm 6.3, hipcc, and dependency wheel availability (torch 2.11, sgl-kernel 0.4.5, flashinfer)

FreeToken ROCm Build

When to use

Verify FreeToken can build on an ROCm host (Dankclaw, similar systems) before committing to the build path.

Steps

Check hardware

rocminfo | grep 'Name.*gfx'      # verify GPU architecture
lsmod | grep amdgpu              # driver loaded
ls /opt/rocm/bin/ | grep hipcc   # compiler available

Check build deps

cmake --version                  # needs >=3.20
python3 --version                # needs >=3.10
gcc --version                    # needs >=9
ninja --version                  # optional but recommended

Verify wheel availability

pip index versions torch         # needs 2.11-2.12 range
pip index versions sgl-kernel    # needs 0.4.5
pip index versions flashinfer-python  # needs >=0.6

Check PyPI for rocm in wheel filenames, or use PyTorch ROCm index.

Build

git clone https://github.com/FlashML-org/FreeToken.git && cd FreeToken
python3 -m venv .venv && source .venv/bin/activate
pip install -e ".[accel]"        # installs fi + sgl extras

Known issues

nvcc missing on Dankclaw — not needed for ROCm build, only for CUDA JIT
sgl-kernel at versioned endpoint may return 404 — use unversioned pip index versions
triton 3.6.0 pins to Linux only

CUDA alternative

If building for CUDA: install sudo pacman -S cuda for nvcc, or use pre-built CUDA wheels that ship pre-compiled kernels.

1.7 KiB Raw Blame History