15 lines
2.2 KiB
Markdown
15 lines
2.2 KiB
Markdown
# [How Transformer LLMs Work](https://www.deeplearning.ai/short-courses/how-transformer-llms-work/?utm_campaign=handsonllm-launch&utm_medium=partner)
|
|
|
|
In this course, we take the content from the book and enhance it through a short course on the main components of what makes a Transformer LLM. This **highly animated** course, will further enhance the intuition you get from the book's content.
|
|
|
|
<p align="center">
|
|
<a href="https://www.deeplearning.ai/short-courses/how-transformer-llms-work/?utm_campaign=handsonllm-launch&utm_medium=partner"><img src="../images/dlai.png" width="50%" height="50%"></a>
|
|
</p>
|
|
|
|
## What you'll learn
|
|
|
|
* Gain an understanding of the key components of transformers, including tokenization, embeddings, self-attention, and transformer blocks, to build a strong technical foundation.
|
|
* Understand recent transformer improvements to the attention mechanism such as KV cache, multi-query attention, grouped query attention, and sparse attention.
|
|
* Compare tokenization strategies used in modern LLMS and explore transformers in the Hugging Face Transformers library.
|
|
|