Card: say how the test error is computed and how to load the checkpoint

README.md

@@ -58,13 +58,16 @@ baseline curve: the window's Watterson estimate of log10 Ne plus a fixed offset
   3 × 10⁻⁴, cosine decay to 5% of it over the 12 epochs, weight decay 10⁻⁴, gradient-norm
   clipping at 1, one update per 32 windows. The last epoch had the lowest validation error, and
   its checkpoint is `final/checkpoint.pt`.
-- **Test error.** RMSE of log10 Ne over the 64 intervals of the 500 test windows: 0.287.
+- **Test error.** 0.287: the root mean squared error of log10 Ne over all 64 intervals of the
+  500 test windows taken together, from `final/test_predictions.npz`.
 
 ## Running it
 
 The network reads inputs built by the NeCast code (summary statistics, PSMC+ posteriors and the
 site encoder's input), and its checkpoint is loaded by that code. The code is being prepared for
-release; its link will be added here. The inputs the network read for every simulated and real
+release; its link will be added here. `final/checkpoint.pt` is a plain PyTorch file:
+`torch.load(path, map_location="cpu", weights_only=True)` returns a dictionary whose
+`state_dict` holds the weights. The inputs the network read for every simulated and real
 window in the paper are in `Larrivhan/NeCast-simulations`, `Larrivhan/NeCast-benchmark` and
 `Larrivhan/NeCast-1000G`.