Responsible Generative AI and Local LLMs

سرفصل های دوره

In this course, MLOps expert Noah Gift guides you through mastering the theory of Generative AI and using local LLMs like Mistral, llamafile, Candle, and Lorax. Learn about profit sharing concepts, the tragedy of the commons, and game theory as it relates to generative AI. Dive into perfect competition, negative externalities, and how to fine tune Mistral with Ludwig. Find out how to get started with llamafile and how to execute Hello World in Candle. Explore Rust and Candle, as well as how to transcribe audio with Whisper. Plus, learn how to use Rust for LLMs.

This course was created by Noah Gift. We are pleased to host this training in our library.

01 - 1. Responsible Generative AI and Local LLMs

01 - Coding ELO in Python

02 - Coding ELO in Rust

03 - Coding ELO in R

04 - Coding ELO in Julia

05 - Profit sharing concepts

06 - Tragedy of the commons

07 - Deploying LLMs with Lorax and SkyPilot

08 - Fine-tune Mistral and Ludwig

09 - Game theory in generative AI

10 - Perfect competition

11 - Negative externalities

12 - Regulatory entrepreneurship

13 - Creating reinforcement bias

14 - Getting started with Mozilla llamafile

15 - Developing cosmopolitan

16 - Building blocks for generative AI with whisper.cpp

17 - Transcribing with Whisper

18 - Portable phrase CLI

19 - Candle hello world

20 - Exploring StarCoder in Rust

21 - Whisper Candle transcriber

22 - Local system metrics

23 - Exploring remote development on AWS

24 - Rust for large language models (LLMs)

25 - The continuous build binary

26 - Serverless inference

27 - Rust CLI inference

28 - Rust chat inference

29 - The chat loop with StarCoder

30 - Invoke an LLM on an AWS G5 instance, part 1

31 - Invoke an LLM on an AWS G5 instance, part 2

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تولید کننده: LinkedIn Learning (Lynda)