v0.1.9 — safer bundled demo defaults for standalone mode

Why this exists

v0.1.7+ runs Pixal3D in ComfyUI Desktop's .venv (standalone mode) where
comfy-aimdo is loaded and pre-allocates a 16 GB cudaMallocAsync cast
buffer on top of Pixal3D's own ~14 GB of weights + activations. The old
v0.1.3 demo defaults (16/16/16 steps, max_num_tokens=65536,
low_vram=False) were tuned for pozzettiandrea's TRELLIS2 worker
subprocess where mmgp is NOT loaded — peak ~14 GB. In standalone mode
the same workflow OOMs at ~29-30 GB on a 5090 (34 GB ceiling), specifically
in get_proj_cond_shape's NAF attention at shape-1024 resolution.

What changed

Bundled workflow widget defaults (both pixal3d_image_to_mesh.json and
pixal3d_image_to_mesh_with_external_rembg.json):

Widget	Was	Now
low_vram	false	true
max_num_tokens	65536	32768

These are the standalone-mode-safe settings that fit on 16-24 GB cards.
On 32 GB+ cards (RTX 5090, A6000-class), flip low_vram back to false
in the widget to cut wall time roughly in half.

The in-workflow Note node explains both the new defaults and the
flip-to-low_vram=false speed-up path.

README

The "Memory + performance" table is rewritten for standalone-mode
reality — all peak-VRAM numbers now reflect what users actually
measure. A new bullet calls out the comfy-aimdo cast-buffer tax
explicitly so the next Googler who hits "OOM on demo workflow"
lands directly on the cause.

What didn't change

No code changes — pyproject.toml version bump only. v0.1.8's runtime
device-placement fix + v0.1.7's mmgp / snapshot_download / install
fallback all carry forward.

Full Changelog: v0.1.8...v0.1.9