point quick-start one-liner at demos/example_sr_op.py

README.md

@@ -50,7 +50,6 @@ All models sample with **50 flow-matching steps, cfg = 1.0** (the paper eval set
 | `shared/git10m_quad_meta.json` | metadata | 1.7 GB | — | Git-10M split metadata (paper eval) |
 | `shared/hierarchy_index_quad.pkl` | metadata | 0.6 GB | — | Parent↔child quadtree index (paper eval) |
 | `dinov3_vitl16_pretrain_sat493m-eadcf0ff.pth` | DINOv3 ViT-L/16 (SAT-493M) | 1.2 GB | — | Frozen conditioning encoder for SR |
-| `example_sr_op.py` | script | — | — | Runnable quick start (below) |
 
 The `ablations/` folder holds additional checkpoints used only to reproduce the paper's ablation
 table (see the [code repo](https://github.com/mvrl/genesis)'s `docs/EVALUATION.md`).
@@ -106,11 +105,11 @@ Every input and output lands in `logs/example_sr_op/`, numbered in pipeline orde
 tile, SR input/output, masked OP input, outpainted OP output — so it's obvious which quadrants
 were given and which were synthesized.
 
-Or as a one-liner — download [`example_sr_op.py`](example_sr_op.py) from this repo into the
-checkout root and run:
+Or as a one-liner, using the copy shipped in the code repo —
+[`demos/example_sr_op.py`](https://github.com/mvrl/genesis/blob/main/demos/example_sr_op.py):
 
 ```bash
-python example_sr_op.py
+python demos/example_sr_op.py
 ```
 
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