Book Image

LLMs Under the Hood – Building Models for Your Unique Use Cases [Video]

By : Maxime Labonne, Denis Rothman, Abi Aryan
Book Image

LLMs Under the Hood – Building Models for Your Unique Use Cases [Video]

By: Maxime Labonne, Denis Rothman, Abi Aryan

Overview of this book

This in-depth masterclass provides end-to-end coverage of developing enterprise-grade LLMs tailored to your unique use cases. Led by experts Maxime Labonne, Dennis Rothman, and Abi Aryan, this video delivers the advanced skills needed to architect performant LLMs that deliver real business impact. You'll learn how to make crucial architecture decisions, select optimal model types, configure hyperparameters, and curate quality training data. Discover professional techniques for pre-training, iterative fine-tuning, and rigorous model evaluation. The instructors reveal insider strategies to productionize your LLMs smoothly, monitor them proactively, and maintain optimal performance post-deployment. Following a structured curriculum spanning the complete LLM lifecycle, this masterclass empowers you with hands-on skills to build, refine, and deploy large language models with confidence. Turbocharge your generative AI initiatives and get the practical knowledge needed to create LLMs that solve complex challenges for your organization.

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LLMs Under the Hood – Building Models for Your Unique Use Cases [Video]
Maxime Labonne | Denis Rothman | Abi Aryan
Jan, 2024 | 4 hours 2 minutes
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Table of Contents (1 chapters)
Free Chapter
1
LLMs Under the Hood
Opening Keynote: Demystifying LLMs – Building, Engineering, and Deploying
Architecting LLMs - Text Generation, Code Interpretation, and More
Modeling LLMs: Input Data, Pre-Training, Fine-Tuning, and Model Evaluation
Productionizing LLMs - Prepare for Production
Chapter 1
LLMs Under the Hood
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Section 2
Architecting LLMs - Text Generation, Code Interpretation, and More
When developing generative AI applications, the choice of the right language model is nothing short of pivotal. You're presented with two distinct paths: harnessing an existing model or embarking on the journey to train a new one from the ground up. Yet, for seasoned professionals or for beginners, mastering the inner workings of LLMs is paramount before you take that all-important step. In this tech session, Denis Rothman (AI ethicist and innovator) will be your guide to cutting through the noise and diving headfirst into the world of LLMs. DALL-E 2 API Example: https://colab.research.google.com/github/Denis2054/Transformers-for-NLP-2nd-Edition/blob/main/Chapter17/Getting_Started_with_the_DALL_E_2_API.ipynb. Visualize Self Attention: https://colab.research.google.com/github/Denis2054/Transformers-for-NLP-2nd-Edition/blob/main/Chapter14/BertViz.ipynb. The Math Behind: https://colab.research.google.com/github/Denis2054/Transformers-for-NLP-2nd-Edition/blob/main/Chapter02/Multi_Head_Attention_Sub_Layer.ipynb. State of the art LLMs: https://colab.research.google.com/github/Denis2054/Transformers-for-NLP-2nd-Edition/blob/main/Chapter17/Getting_Started_OpenAI_GPT_4.ipynb. Summarize Text with T5: https://colab.research.google.com/github/Denis2054/Transformers-for-NLP-2nd-Edition/blob/main/Chapter08/Summarizing_Text_with_T5.ipynb. Summarize with ChatGPT: https://colab.research.google.com/github/Denis2054/Transformers-for-NLP-2nd-Edition/blob/main/Chapter09/Summarizing_with_ChatGPT.ipynb. Denis' book URL: https://www.amazon.com/dp/1803247339/. Link to the deck: https://packt.link/eDwvj.
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