Transformers In Action Meap V7 2024 Chapters 1 To 9 Of 10 Nicole Koenigstein by Nicole Koenigstein instant download after payment.

Transformers are the superpower behind large language models (LLMs) like ChatGPT, Bard, and LLAMA. Transformers in Action gives you the insights, practical techniques, and extensive code samples you need to adapt pretrained transformer models to new and exciting tasks.
 
Inside Transformers in Action you’ll learn:
    How transformers and LLMs work
    Adapt HuggingFace models to new tasks
    Automate hyperparameter search with Ray Tune and Optuna
    Optimize LLM model performance
    Advanced prompting and zero/few-shot learning
    Text generation with reinforcement learning
    Responsible LLMs
 
Technically speaking, a “Transformer” is a neural network model that finds relationships in sequences of words or other data by using a mathematical technique called attention in its encoder/decoder components. This setup allows a transformer model to learn context and meaning from even long sequences of text, thus creating much more natural responses and predictions. Understanding the transformers architecture is the key to unlocking the power of LLMs for your own AI applications.
 
This comprehensive guide takes you from the origins of transformers all the way to fine-tuning an LLM for your own projects. Author Nicole Königstein demonstrates the vital mathematical and theoretical background of the transformer architecture practically through executable Jupyter notebooks, illuminating how this amazing technology works in action.