Главная
Study mode:
on
1
Intro
2
Workshop Overview
3
Models
4
Open AI
5
GPT
6
Why Custom Language Models
7
Task Framework
8
Helm
9
Challenges
10
Data Synthesis Pipeline
11
Data Synthesis Blog
12
Prompt Engineering Notebook
13
Prompt Generator
14
Memory Footprint
15
Notebook
16
Tokenization
17
Naive Data Parallelization
18
Parameter Efficient Fine Tuning
19
Memory Profile
20
Memory Footprint Comparison
21
More Memory Usage Tricks
Description:
Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only! Grab it Explore the world of custom AI models in this comprehensive workshop presented by Mark Huang at LLMs in Pod Con. Discover how to develop specialized AI applications by leveraging fine-tuning techniques and data-driven approaches like self-refinement. Learn about the challenges of differentiation in a landscape where foundational models are widely accessible, and gain insights into creating unique AI products capable of solving previously unattainable problems. Delve into topics such as task frameworks, data synthesis pipelines, prompt engineering, memory optimization, and parameter-efficient fine-tuning. Benefit from Mark's extensive experience as a Co-founder and Head of AI at Preemo, as well as his background in machine learning at Splunk and Box.

The Next Million AI Apps - Developing Custom Models for Specialized Tasks

MLOps.community
Add to list