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The Ultimate Guide to Snowpark

You're reading from   The Ultimate Guide to Snowpark Design and deploy Snowflake Snowpark with Python for efficient data workloads

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Product type Paperback
Published in May 2024
Publisher Packt
ISBN-13 9781805123415
Length 254 pages
Edition 1st Edition
Languages
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Authors (2):
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Shankar Narayanan SGS Shankar Narayanan SGS
Author Profile Icon Shankar Narayanan SGS
Shankar Narayanan SGS
Vivekanandan SS Vivekanandan SS
Author Profile Icon Vivekanandan SS
Vivekanandan SS
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Toc

Table of Contents (14) Chapters Close

Preface 1. Part 1: Snowpark Foundation and Setup FREE CHAPTER
2. Chapter 1: Discovering Snowpark 3. Chapter 2: Establishing a Foundation with Snowpark 4. Part 2: Snowpark Data Workloads
5. Chapter 3: Simplifying Data Processing Using Snowpark 6. Chapter 4: Building Data Engineering Pipelines with Snowpark 7. Chapter 5: Developing Data Science Projects with Snowpark 8. Chapter 6: Deploying and Managing ML Models with Snowpark 9. Part 3: Snowpark Applications
10. Chapter 7: Developing a Native Application with Snowpark 11. Chapter 8: Introduction to Snowpark Container Services 12. Index 13. Other Books You May Enjoy

Deploying LLMs with Snowpark

Modern enterprises increasingly demand that LLMs be harnessed with proprietary data. Open source and proprietary models play pivotal roles in enabling this transition. However, the main challenge is finding a robust platform capable of effectively leveraging LLMs’ power. Snowflake empowers organizations to apply near-magical generative AI transformations to their data. By leveraging advanced LLM models within Snowflake, organizations can efficiently operate with large volumes of data, enabling generative AI use cases. In this section, we will discuss deploying LLM models within Snowpark Container Services.

In this walk-through, we’ll explore how to harness publicly accessible data to demonstrate the transformative capabilities of Snowflake’s ecosystem by deploying the Llama 2 LLM from the Hugging Face repository.

Note

Llama 2 by Meta, housed within Hugging Face’s library, epitomizes advanced natural language processing...

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