Frank
689228e60d
Second half of the purge (the first covered the persona, AGENTS.md, README.md, and the distillation of the per-host pages). Every remaining identifier is gone: hostname, both LAN addresses, and the Wi-Fi SSID. 34 count-checked substitutions across 22 files — indexes, tool/research pages, the inventory census, the changelog, one generated HTML report, and five managed skills. Facts kept, names dropped: a history entry keeps its four-page listing as a nameless summary, the syslog excerpts keep every timestamp and line, and the census keeps the .zcompdump rows (the zsh version stamps are the useful part, the hostname was not). Deliberately unchanged: install.sh's --host case list and the packages/<hostname>.pkgs filename, where the hostname is the lookup key. Left out of scope by Frank's call: agent/memories/** — past-session records the learn pipeline rewrites. kb-lint: 0 violations. Residual grep for the hostname, its two IPs, and the SSID across omp-docs/ and agent/managed-skills/: no hits.
1.3 KiB
1.3 KiB
name, description
| name | description |
|---|---|
| freetoken-dankclaw-build | Build FreeToken on Dankclaw — installs CUDA toolkit, sets CUDA_HOME, handles nvcc/CUDA version mismatch |
Build FreeToken on Dankclaw
Prerequisites
- CUDA toolkit:
sudo apt install nvidia-cuda-toolkit(gives nvcc at /usr/bin, libcudart at /usr/lib/x86_64-linux-gnu/) - uv: installed at /home/dank/.local/bin/uv (or install via
curl -LsSf https://astral.sh/uv/install.sh | sh) - CMake, git, Python >= 3.10 — all present
Build steps
cd /home/dank
git clone https://github.com/FlashML-org/FreeToken.git # or cd into existing
cd FreeToken
uv venv && source .venv/bin/activate
export CUDA_HOME=/usr
export FREETOKEN_ALLOW_CUDA_MISMATCH=1 # nvcc 12.4 + torch cu130 is safe
uv pip install -e ".[accel]"
Verification
ft --version
python3 -c "
from freetoken.checkpoint import ftw
import torch
t = torch.randn(3,4,dtype=torch.float16)
print(ftw._dtype_str(t.dtype), ftw._elsize(t.dtype))
"
Key notes
- FTW format is dtype-agnostic: FP16, BF16 (default), FP32, FP8 all work
- GGUF support: only Gemma4GGUFForCausalLM
- GGML types: F32/F16/BF16 (native views), Q4_0/Q6_K (dequant), Q8_0 (listed, no dequant)
- The NVIDIA driver modules may not be loaded at build time (NVML warning) — not a problem for the build itself