Update README.md

README.md

@@ -54,13 +54,3 @@ gen_model = nnx.merge(graphdef, checkpointer.restore_ema(params))
 
 `restore_ema` reads only `ema_params` and `extra`, and applies the same bias
 correction the training loop uses for evaluation.
-
-## Reproducing
-
-```bash
-uv run python tutorials/scripts/train_conditioning_checkpoints.py
-```
-
-The script mirrors the notebook's model definitions and PRNG chain, so it
-reproduces these exact weights. A checkpoint pins the parameter structure: if a
-notebook's network changes, re-run the script and re-upload.