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Home > Data > Artificial Intelligence > Harnessing Open Source LLMs and ChatGPT with Minimal Code [Video]
Harnessing Open Source LLMs and ChatGPT with Minimal Code [Video]
Harnessing Open Source LLMs and ChatGPT with Minimal Code [Video]

Harnessing Open Source LLMs and ChatGPT with Minimal Code: Explore Large Language Models with Open Source Innovations like LLama3 and ChatGPT

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Profile Icon Mr. Daniel Weikert
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$79.99
Video Jul 2024 1 hours 59 minutes 1st Edition
Video
$79.99
Subscription
Free Trial
Renews at $19.99p/m
Arrow left icon
Profile Icon Mr. Daniel Weikert
Arrow right icon
$79.99
Video Jul 2024 1 hours 59 minutes 1st Edition
Video
$79.99
Subscription
Free Trial
Renews at $19.99p/m
Video
$79.99
Subscription
Free Trial
Renews at $19.99p/m

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Key benefits

  • No-code solutions for running open-source models
  • Advanced Python techniques for streaming responses and function calling
  • Insights into using llama3 model with a web interface

Description

Welcome to the captivating world of Large Language Models (LLMs)! This course is designed to guide you through the fascinating landscape of LLMs, encompassing both no-code and low-code solutions powered by Python. We begin by equipping you with the necessary software to operate these models locally, enabling you to explore various open-source models, including Google’s Gemma:7b and Llama3, without the need for an internet connection. In the advanced section, you will delve into using Python for streaming responses from open-source LLMs and integrating with the official OpenAI API. The course covers low code solutions for streaming ChatGPT responses and introduces function calling within ChatGPT models. You'll also learn about the llama3 model and how to interface it with Python for web applications. Throughout the course, you'll gain experience fetching responses in both batch and streaming modes, and we will jointly develop a small web frontend using Streamlit for our streaming LLM API. By the end of the course, you'll be equipped to run open-source LLMs locally and leverage their capabilities to the fullest.

What you will learn

  • Configure and run local LLMs
  • Use local server API endpoints for open-source models
  • Integrate and utilize OpenAI API with Python
  • Implement low-code solutions for streaming ChatGPT responses
  • Operate the llama3 model using Python web interfaces
  • Develop a small web frontend for streaming LLM APIs using Streamlit
  • Experiment with various open-source models, understanding their capabilities and limitations

Product Details

Country selected
Publication date, Length, Edition, Language, ISBN-13
Publication date : Jul 24, 2024
Length 1 hours 59 minutes
Edition : 1st Edition
Language : English
ISBN-13 : 9781836642534
Category :
Data
Languages :
Python (Intermediate)
Concepts :
Artificial Intelligence
Tools :
Ollama (Intermediate) , ChatGPT (Intermediate)

What do you get with a video?

Product feature icon Download this video in MP4 format
Product feature icon Access this title in our online reader with advanced features
Product feature icon DRM FREE - Read whenever, wherever and however you want

Product Details

Publication date : Jul 24, 2024
Length 1 hours 59 minutes
Edition : 1st Edition
Language : English
ISBN-13 : 9781836642534
Category :
Data
Languages :
Python (Intermediate)
Concepts :
Artificial Intelligence
Tools :
Ollama (Intermediate) , ChatGPT (Intermediate)

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Table of Contents

2 Chapters
1. Setting Up and Exploring Local LLMs Chevron down icon Chevron up icon
Download the required Software for the course
No code chat with open-source models locally for free
Running open-source models without code locally in the command line
Openai API preparations
Download python and set env variable in your code editor
Exploring the local Server API endpoint of our open-source model
A different way to use local server API endpoint for open source LLMs with Python
2. Advanced Usage and API Integrations Chevron down icon Chevron up icon
Open Source LLM streaming responses locally with Python API calls
Exploring the official openai API endpoint using Python
Streaming openai chatgpt responses with Python low code
Introduction to function calling with ChatGPT models in Python
Open source llama3 model with web interface in Python
Running No code open source LLMs locally

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About the author

Profile icon Mr. Daniel Weikert
Mr. Daniel Weikert
Daniel Weikert is a 33-year-old entrepreneur, data enthusiast, consultant, and trainer. He is a master's degree holder certified in Power BI, Tableau, Alteryx (Core and Advanced), and KNIME (L1–L3). He is currently working in the business intelligence field and helps companies and individuals obtain vital insights from their data to deliver long-term strategic growth and outpace their competitors. He possesses a fervent dedication to both learning and teaching. His unwavering commitment extends to providing educational services and assisting individuals in achieving their objectives, mastering their fields, and embarking on new career journeys.
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