Mastering LLM Applications with LangChain and Hugging Face. Questo articolo non è disponibile.
Lingua: inglese
Editore: BPB Publications, 2024
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Codice articolo L2-9789365891041
- Titolo
- Mastering LLM Applications with LangChain and Hugging Face
- Autore
- Pathan, Hunaidkhan
- Editore
- BPB Publications
- Anno di pubblicazione
- 2024
- Condizione
- New
- Rilegatura
- PAP
- Lingua
- inglese
- ISBN 10
- 9365891043
- ISBN 13
- 9789365891041
- Peso dell'articolo
- 701 grammi
Description
The book is all about the basics of NLP, generative AI, and their specific component LLM. In this book, we have provided conceptual knowledge about different terminologies and concepts of NLP and NLG with practical hands-on.
This comprehensive book offers a deep dive into the world of NLP and LLMs. Starting with the fundamentals of Python programming and code editors, the book gradually introduces NLP concepts, including text preprocessing, word embeddings, and transformer architectures. You will explore the architecture and capabilities of popular models like GPT-3 and BERT. The book also covers practical aspects of LLM usage for RAG applications using frameworks like LangChain and Hugging Face and deploying them in real world applications. With a focus on both theoretical knowledge and hands-on experience, this book is ideal for anyone looking to master the art of NLP and LLMs. The book also contains AWS Cloud deployment, which will help readers step into the world of cloud computing.
As the book contains both theoretical and practical approaches, it will help the readers to gain confidence in the deployment of LLMs for any use cases, as well as get acquainted with the required generative AI knowledge to crack the interviews.
Key Features
● Covers Python basics, NLP concepts, and terminologies, including LLM and RAG concepts.
● Provides exposure to LangChain, Hugging Face ecosystem, and chatbot creation using custom data.
● Guides on integrating chatbots with real-time applications and deploying them on AWS Cloud.
What you will learn
● Basics of Python, which contains Python concepts, installation, and code editors.
● Foundation of NLP and generative AI concepts and different terminologies being used in NLP and generative AI domain.
● LLMs and their importance in the cutting edge of AI.
● Creating chatbots using custom data using open source LLMs without spending a single penny.
● Integration of chatbots with real-world applications like Telegram.
Who this book is for
This book is ideal for beginners and freshers entering the AI or ML field, as well as those at an intermediate level looking to deepen their understanding of generative AI, LLMs, and cloud deployment.
Table of Contents
1. Introduction to Python and Code Editors
2. Installation of Python, Required Packages, and Code Editors
3. Ways to Run Python Scripts
4. Introduction to NLP and its Concepts
5. Introduction to Large Language Models
6. Introduction of LangChain, Usage and Importance
7. Introduction of Hugging Face, its Usage and Importance
8. Creating Chatbots Using Custom Data with LangChain and Hugging Face Hub
9. Hyperparameter Tuning and Fine Tuning Pre-Trained Models
10. Integrating LLMs into Real-World Applications–Case Studies
11. Deploying LLMs in Cloud Environments for Scalability
12. Future Directions: Advances in LLMs and Beyond
Appendix A: Useful Tips for Efficient LLM Experimentation
Appendix B: Resources and References
The book is all about the basics of NLP, generative AI, and their specific component LLM. In this book, we have provided conceptual knowledge about different terminologies and concepts of NLP and NLG with practical hands-on.
This comprehensive book offers a deep dive into the world of NLP and LLMs. Starting with the fundamentals of Python programming and code editors, the book gradually introduces NLP concepts, including text preprocessing, word embeddings, and transformer architectures. You will explore the architecture and capabilities of popular models like GPT-3 and BERT. The book also covers practical aspects of LLM usage for RAG applications using frameworks like LangChain and Hugging Face and deploying them in real world applications. With a focus on both theoretical knowledge and hands-on experience, this book is ideal for anyone looking to master the art of NLP and LLMs. The book also contains AWS Cloud deployment, which will help readers step into the world of cloud computing.
As the book contains both theoretical and practical approaches, it will help the readers to gain confidence in the deployment of LLMs for any use cases, as well as get acquainted with the required generative AI knowledge to crack the interviews.
Key Features
● Covers Python basics, NLP concepts, and terminologies, including LLM and RAG concepts.
● Provides exposure to LangChain, Hugging Face ecosystem, and chatbot creation using custom data.
● Guides on integrating chatbots with real-time applications and deploying them on AWS Cloud.
What you will learn
● Basics of Python, which contains Python concepts, installation, and code editors.
● Foundation of NLP and generative AI concepts and different terminologies being used in NLP and generative AI domain.
● LLMs and their importance in the cutting edge of AI.
● Creating chatbots using custom data using open source LLMs without spending a single penny.
● Integration of chatbots with real-world applications like Telegram.
Who this book is for
This book is ideal for beginners and freshers entering the AI or ML field, as well as those at an intermediate level looking to deepen their understanding of generative AI, LLMs, and cloud deployment.
Table of Contents
1. Introduction to Python and Code Editors
2. Installation of Python, Required Packages, and Code Editors
3. Ways to Run Python Scripts
4. Introduction to NLP and its Concepts
5. Introduction to Large Language Models
6. Introduction of LangChain, Usage and Importance
7. Introduction of Hugging Face, its Usage and Importance
8. Creating Chatbots Using Custom Data with LangChain and Hugging Face Hub
9. Hyperparameter Tuning and Fine Tuning Pre-Trained Models
10. Integrating LLMs into Real-World Applications–Case Studies
11. Deploying LLMs in Cloud Environments for Scalability
12. Future Directions: Advances in LLMs and Beyond
Appendix A: Useful Tips for Efficient LLM Experimentation
Appendix B: Resources and References
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