llm-introduction-attention-transformer and an assginment of transformer without hollowing

open-machine-learning-jupyter-book/_config.yml

@@ -23,6 +23,7 @@ execute:
     - 'ml-advanced/unsupervised-learning-pca-and-clustering.ipynb'
     - 'ml-advanced/unsupervised-learning.ipynb'
     - 'data-science/data-science-in-the-cloud/the-azure-ml-sdk-way.ipynb'
+    - 'llm/basic/transformer.ipynb'
 
 parse:
   myst_enable_extensions:

open-machine-learning-jupyter-book/_toc.yml

@@ -122,6 +122,14 @@ parts:
   - file: machine-learning-productionization/data-engineering
   - file: machine-learning-productionization/model-training-and-evaluation
   - file: machine-learning-productionization/model-deployment
+- caption: Large Language Models
+  numbered: True
+  chapters:
+  - file: llm/introduction
+  - file: llm/basic/basic
+    sections:
+    - file: llm/basic/attention
+    - file: llm/basic/transformer
 - caption: OTHERS
   numbered: True
   maxdepth: 1
@@ -237,6 +245,7 @@ parts:
     - file: assignments/deep-learning/nlp/getting-start-nlp-with-classification-task
     - file: assignments/deep-learning/nlp/beginner-guide-to-text-preprocessing
     - file: assignments/deep-learning/nlp/news-topic-classification-tasks
+    - file: assignments/llm/basic/transformer-architecture
   - file: slides/introduction
     sections:
     - file: slides/python-programming/python-programming-introduction