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)
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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 3
Modeling LLMs: Input Data, Pre-Training, Fine-Tuning, and Model Evaluation
It's easy to make something cool with LLMs, but very hard to make something production-ready with them. In the next two sessions, Abi Aryan (ML engineer) and Denis Rothman (AI ethicist and innovator) will demonstrate every step of modelling LLMs and take you from concepts to production-ready LLMs. HuggingFace Hub: https://huggingface.co/docs/hub/index#:~:text=Machine%20Learning%20%F0%9F%94%A5.-,The%20Hugging%20Face%20Hub%20is%20a%20platform%20with%20over%20120k,with%20open%2Dsource%20Machine%20Learning. OpenAI Privacy Policy: https://openai.com/policies/privacy-policy. OpenAI's GPT-3: https://lambdalabs.com/blog/demystifying-gpt-3. HuggingFace: https://huggingface.co/autotrain. Finetuning BERT Variant: https://github.com/Denis2054/Transformers-for-NLP-2nd-Edition/blob/main/Bonus/BERT_Fine_Tuning_Sentence_Classification_GPU_Session_2.ipynb. Training BERT Variant: https://github.com/Denis2054/Transformers-for-NLP-2nd-Edition/blob/main/Bonus/Customer_Support_for_X_Session_2.ipynb. Denis' book URL: https://www.amazon.com/dp/1803247339/. Link to the deck: https://packt.link/UamVS.
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