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Large Language Model-Based Solutions
- Author
- Shreyas Subramanian
- Narrator
- Daniel Henning
- Publisher
- Ascent Audio
- Publish Date
- 19 November 2024
- Run Time
- 11 hours 43 minutes
- Format
- Audiobook
What to expect
The author sheds light on techniques for optimizing inference, like model quantization and pruning, as well as different and affordable architectures for typical generative AI (GenAI) applications, including search systems, agent assists, and autonomous agents. You'll also find:
● Effective strategies to address the challenge of the high computational cost associated with LLMs
● Assistance with the complexities of building and deploying affordable generative AI apps, including tuning and inference techniques
● Selection criteria for choosing a model, with particular consideration given to compact, nimble, and domain-specific models
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Details
- Author
- Shreyas Subramanian
- Narrator
- Daniel Henning
- Duration
- 11 hours 43 minutes
- Release Date
- 19 November 2024
- ISBN
- 9781663749284
- Format
- Audiobook
- Publisher
- Ascent Audio
- Genre
- Mathematical theory of computation, Machine learning, Natural language and machine translation
Synopsis
In Large Language Model-Based Solutions: How to Deliver Value with Cost-Effective Generative AI Applications, Principal Data Scientist at Amazon Web Services, Shreyas Subramanian, delivers a practical guide for developers and data scientists who wish to build and deploy cost-effective large language model (LLM)-based solutions. In the book, you'll find coverage of a wide range of key topics, including how to select a model, pre- and post-processing of data, prompt engineering, and instruction fine-tuning.The author sheds light on techniques for optimizing inference, like model quantization and pruning, as well as different and affordable architectures for typical generative AI (GenAI) applications, including search systems, agent assists, and autonomous agents. You'll also find:● Effective strategies to address the challenge of the high computational cost associated with LLMs● Assistance with the complexities of building and deploying affordable generative AI apps, including tuning and inference techniques● Selection criteria for choosing a model, with particular consideration given to compact, nimble, and domain-specific models
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