Falcata 1.0.2

Patch release. pip install falcata now resolves to 1.0.2.

Fixed

• Source builds on Kaggle/Colab images — the build died with Target "CUDA::cuda_driver" not found on images that ship the driver's libcuda.so.1 in a nonstandard path with no toolkit stubs. The build now locates the driver library directly. (Reported from a Kaggle P100 notebook — thanks!)
• CUDA 13 toolkits — CUDA 13 removed compilation for pre-sm_75 GPUs; the build now fails at configure time with the remedy spelled out (use a CUDA 12.x toolkit) instead of dying cryptically mid-compile, and no longer silently targets sm_75 on older GPUs via nvcc 13's injected default.
• Saved models are device-portable — an automatically chosen device is no longer written into the model file, and save/load round-trips are bit-identical again.
• The "sparse features not supported" warning no longer fires on dense data; it appears (as an Info about memory) only when a column would actually have used sparse storage.

Changed

• device_type unset now means auto: a CUDA build with a usable GPU trains on it (one Info line says so); no GPU or an unsupported one falls back to CPU. Pass device_type explicitly to pin either choice.
• The prebuilt wheel now covers the P100 — the Pascal slot ships sm_60 cubins (which every Pascal card runs) instead of sm_61, at no size cost. Wheel coverage: sm_60 through sm_120.