diff --git a/ch05/03_bonus_pretraining_on_gutenberg/README.md b/ch05/03_bonus_pretraining_on_gutenberg/README.md
index 1c0f94d..79b63bf 100644
--- a/ch05/03_bonus_pretraining_on_gutenberg/README.md
+++ b/ch05/03_bonus_pretraining_on_gutenberg/README.md
@@ -118,4 +118,4 @@ Note that this code focuses on keeping things simple and minimal for educational
 5. Add a more advanced logger (for example, Weights and Biases) to view the loss and validation curves live
 6. Add distributed data parallelism (DDP) and train the model on multiple GPUs (see section *A.9.3 Training with multiple GPUs* in appendix A; [DDP-script.py](../../appendix-A/03_main-chapter-code/DDP-script.py)).
 7. Swap the from scratch `MultiheadAttention` class in the `previous_chapter.py` script with the efficient `MHAPyTorchScaledDotProduct` class implemented in the [Efficient Multi-Head Attention Implementations](../../ch03/02_bonus_efficient-multihead-attention/mha-implementations.ipynb) bonus section, which uses Flash Attention via PyTorch's `nn.functional.scaled_dot_product_attention` function.
-
+8. Speeding up the training by optimizing the model via [torch.compile](https://pytorch.org/tutorials/intermediate/torch_compile_tutorial.html) (`model = torch.compile`) or [thunder](https://github.com/Lightning-AI/lightning-thunder) (`model = thunder.jit(model)`).