mirror of
https://github.com/rasbt/LLMs-from-scratch.git
synced 2025-08-31 03:50:23 +00:00
Update bonus section formatting (#400)
This commit is contained in:
parent
35ecca0feb
commit
6a9bedc2ec
@ -1,8 +1,15 @@
|
||||
# Chapter 1: Understanding Large Language Models
|
||||
|
||||
|
||||
|
||||
## Main Chapter Code
|
||||
|
||||
There is no code in this chapter.
|
||||
|
||||
<br>
|
||||
|
||||
|
||||
## Bonus Materials
|
||||
|
||||
As optional bonus material, below is a video tutorial where I explain the LLM development lifecycle covered in this book:
|
||||
|
||||
<br>
|
||||
|
@ -1,10 +1,11 @@
|
||||
# Chapter 2: Working with Text Data
|
||||
|
||||
|
||||
|
||||
## Main Chapter Code
|
||||
|
||||
- [01_main-chapter-code](01_main-chapter-code) contains the main chapter code and exercise solutions
|
||||
|
||||
|
||||
## Bonus Materials
|
||||
|
||||
- [02_bonus_bytepair-encoder](02_bonus_bytepair-encoder) contains optional code to benchmark different byte pair encoder implementations
|
||||
|
@ -1,9 +1,11 @@
|
||||
# Chapter 3: Coding Attention Mechanisms
|
||||
|
||||
|
||||
## Main Chapter Code
|
||||
|
||||
- [01_main-chapter-code](01_main-chapter-code) contains the main chapter code.
|
||||
|
||||
|
||||
## Bonus Materials
|
||||
|
||||
- [02_bonus_efficient-multihead-attention](02_bonus_efficient-multihead-attention) implements and compares different implementation variants of multihead-attention
|
||||
|
@ -1,10 +1,13 @@
|
||||
# Chapter 4: Implementing a GPT Model from Scratch to Generate Text
|
||||
|
||||
|
||||
## Main Chapter Code
|
||||
|
||||
- [01_main-chapter-code](01_main-chapter-code) contains the main chapter code.
|
||||
|
||||
## Optional Code
|
||||
|
||||
## Bonus Materials
|
||||
|
||||
- [02_performance-analysis](02_performance-analysis) contains optional code analyzing the performance of the GPT model(s) implemented in the main chapter.
|
||||
- [02_performance-analysis](02_performance-analysis) contains optional code analyzing the performance of the GPT model(s) implemented in the main chapter
|
||||
- [ch05/07_gpt_to_llama](../ch05/07_gpt_to_llama) contains a step-by-step guide for converting a GPT architecture implementation to Llama 3.2 and loads pretrained weights from Meta AI (it might be interesting to look at alternative architectures after completing chapter 4, but you can also save that for after reading chapter 5)
|
||||
|
||||
|
@ -1,9 +1,11 @@
|
||||
# Chapter 5: Pretraining on Unlabeled Data
|
||||
|
||||
|
||||
## Main Chapter Code
|
||||
|
||||
- [01_main-chapter-code](01_main-chapter-code) contains the main chapter code
|
||||
|
||||
|
||||
## Bonus Materials
|
||||
|
||||
- [02_alternative_weight_loading](02_alternative_weight_loading) contains code to load the GPT model weights from alternative places in case the model weights become unavailable from OpenAI
|
||||
|
@ -1,10 +1,11 @@
|
||||
# Chapter 6: Finetuning for Classification
|
||||
|
||||
|
||||
|
||||
## Main Chapter Code
|
||||
|
||||
- [01_main-chapter-code](01_main-chapter-code) contains the main chapter code
|
||||
|
||||
|
||||
## Bonus Materials
|
||||
|
||||
- [02_bonus_additional-experiments](02_bonus_additional-experiments) includes additional experiments (e.g., training the last vs first token, extending the input length, etc.)
|
||||
|
@ -1,9 +1,11 @@
|
||||
# Chapter 7: Finetuning to Follow Instructions
|
||||
|
||||
|
||||
## Main Chapter Code
|
||||
|
||||
- [01_main-chapter-code](01_main-chapter-code) contains the main chapter code and exercise solutions
|
||||
|
||||
|
||||
## Bonus Materials
|
||||
|
||||
- [02_dataset-utilities](02_dataset-utilities) contains utility code that can be used for preparing an instruction dataset
|
||||
|
Loading…
x
Reference in New Issue
Block a user