diff --git a/README.md b/README.md
index 9a9516c7..b9b3bdf2 100644
--- a/README.md
+++ b/README.md
@@ -52,13 +52,13 @@ Alternatively, you can view this and other files on GitHub at [https://github.co
| Ch 3: Coding Attention Mechanisms | - [ch03.ipynb](ch03/01_main-chapter-code/ch03.ipynb)
- [multihead-attention.ipynb](ch03/01_main-chapter-code/multihead-attention.ipynb) (summary)
- [exercise-solutions.ipynb](ch03/01_main-chapter-code/exercise-solutions.ipynb)| [./ch03](./ch03) |
| Ch 4: Implementing a GPT Model from Scratch | - [ch04.ipynb](ch04/01_main-chapter-code/ch04.ipynb)
- [gpt.py](ch04/01_main-chapter-code/gpt.py) (summary)
- [exercise-solutions.ipynb](ch04/01_main-chapter-code/exercise-solutions.ipynb) | [./ch04](./ch04) |
| Ch 5: Pretraining on Unlabeled Data | - [ch05.ipynb](ch05/01_main-chapter-code/ch05.ipynb)
- [gpt_train.py](ch05/01_main-chapter-code/gpt_train.py) (summary)
- [gpt_generate.py](ch05/01_main-chapter-code/gpt_generate.py) (summary)
- [exercise-solutions.ipynb](ch05/01_main-chapter-code/exercise-solutions.ipynb) | [./ch05](./ch05) |
-| Ch 6: Finetuning for Text Classification | Q2 2024 | ... |
+| Ch 6: Finetuning for Text Classification | - [ch06.ipynb](ch05/01_main-chapter-code/ch06.ipynb) | [./ch06](./ch06) |
| Ch 7: Finetuning with Human Feedback | Q2 2024 | ... |
-| Ch 8: Using Large Language Models in Practice | Q2/3 2024 | ... |
| Appendix A: Introduction to PyTorch | - [code-part1.ipynb](appendix-A/01_main-chapter-code/code-part1.ipynb)
- [code-part2.ipynb](appendix-A/01_main-chapter-code/code-part2.ipynb)
- [DDP-script.py](appendix-A/01_main-chapter-code/DDP-script.py)
- [exercise-solutions.ipynb](appendix-A/01_main-chapter-code/exercise-solutions.ipynb) | [./appendix-A](./appendix-A) |
| Appendix B: References and Further Reading | No code | - |
| Appendix C: Exercise Solutions | No code | - |
| Appendix D: Adding Bells and Whistles to the Training Loop | - [appendix-D.ipynb](appendix-D/01_main-chapter-code/appendix-D.ipynb) | [./appendix-D](./appendix-D) |
+| Appendix E: Parameter-efficient Finetuning with LoRA | - Q2 2024 | ... |