- Linux: CUDA detection via /usr/local/cuda*, Ninja preferred - macOS: Metal backend auto-enabled (llama.cpp default), no CUDA - Windows: CUDA via CUDA_PATH env and toolkit dirs, VS generator fallback, binaries in build/bin/Release/, copy instead of symlink - Reuse existing source (don't re-clone if CMakeLists.txt present) - Both llama-server and llama-quantize verified and built |
||
|---|---|---|
| .. | ||
| backend | ||
| frontend | ||
| __init__.py | ||
| install_python_stack.py | ||
| LICENSE.AGPL-3.0 | ||
| setup.bat | ||
| setup.ps1 | ||
| setup.sh | ||
| Unsloth_Studio_Colab.ipynb | ||