Parameter-Efficient Fine-Tuning Courses and Certifications

Association for Computing Machinery (ACM)

When MOE Meets LLMs: Parameter Efficient Fine-tuning for Multi-task Medical Applications - Lecture 1

Explore parameter-efficient fine-tuning techniques for multi-task medical applications using Mixture of Experts and Large Language Models.

• YouTube
• 14 minutes
• On-Demand
• Free Video

Association for Computing Machinery (ACM)

IISAN: Efficiently Adapting Multimodal Representation for Sequential Recommendation - M2.6

Explore efficient multimodal representation adaptation for sequential recommendations using decoupled PEFT in this innovative research presentation.

• YouTube
• 14 minutes
• On-Demand
• Free Video

Generative AI Engineering and Fine-Tuning Transformers

13 ratings at Coursera

Explore transformers, fine-tuning, and PEFT techniques for LLMs. Gain hands-on experience with Hugging Face and PyTorch to develop job-ready generative AI engineering skills.

• Coursera
• 8 hours 2 minutes
• On-Demand
• Free Online Course (Audit)

Unify

ReFT: Representation Finetuning for Language Models Explained

Explore ReFT, a novel approach to fine-tuning language models by modifying internal representations, achieving efficiency with fewer parameters than traditional methods.

• YouTube
• 1 hour 7 minutes
• On-Demand
• Free Video

Discover AI

Spectral Analysis of LoRA vs Full Fine-Tuning in Language Models

Delve into the technical comparison between LoRA and full fine-tuning methods for language models, exploring their structural differences, spectral properties, and impact on model performance.

• YouTube
• 28 minutes
• On-Demand
• Free Video

Anyscale

Fine-Tuning Large Language Models at Scale - Workday's Approach

Dive into Workday's innovative approach to fine-tuning LLMs securely in a multi-tenant environment, addressing GPU scarcity and data access controls using PEFT techniques and KubeRay's autoscaling capabilities.

• YouTube
• 31 minutes
• On-Demand
• Free Video

Graham Neubig

Instruction Tuning in Advanced Natural Language Processing - Lecture 6

Explore advanced NLP concepts: multi-tasking, fine-tuning, instruction tuning, parameter-efficient methods, datasets, and synthetic data generation for enhanced language models.

• YouTube
• 1 hour 6 minutes
• On-Demand
• Free Video

CodeEmporium

LoRA - Low Rank Adaptation for Parameter Efficient Fine-Tuning

Dive into parameter-efficient fine-tuning with LoRA, exploring low-rank matrices, adapters, and techniques to optimize neural network storage and performance while maintaining accuracy.

• YouTube
• 29 minutes
• On-Demand
• Free Video

MLOps.community

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

Develop custom AI models using fine-tuning and data-driven techniques to create differentiated products solving previously unattainable problems.

• YouTube
• 1 hour 3 minutes
• On-Demand
• Free Video

Discover AI

Fourier-Enhanced Fine-Tuning Vision Language Models Using PEFT-VFPT

Discover how Visual Fourier Prompt Tuning revolutionizes vision model fine-tuning by integrating Fast Fourier Transform, enhancing adaptability and accuracy while using minimal trainable parameters.

• YouTube
• 27 minutes
• On-Demand
• Free Video

CodeEmporium

LLM Fine-Tuning - Explained

Explore parameter efficient fine-tuning techniques for large language models, including adapters, prefix-tuning, and LoRA. Learn their importance, implementation details, and performance evaluation.

• YouTube
• 23 minutes
• On-Demand
• Free Video

Shaw Talebi

Fine-tuning Large Language Models (LLMs) with Example Code

Learn to fine-tune large language models with practical Python examples. Explore techniques like LoRA for efficient parameter tuning and implement a text classification model using distilBERT.

• YouTube
• 28 minutes
• On-Demand
• Free Video

MIT HAN Lab

Efficient Fine-tuning and Prompt Engineering - Lecture 20

Explore efficient fine-tuning techniques and prompt engineering strategies for optimizing large language models in machine learning applications.

• YouTube
• 1 hour 18 minutes
• On-Demand
• Free Video

MIT HAN Lab

Efficient Fine-tuning and Prompt Engineering - Lecture 20

Explore efficient fine-tuning techniques and prompt engineering strategies for optimizing large language models in machine learning applications.

• YouTube
• 1 hour 17 minutes
• On-Demand
• Free Video

Toronto Machine Learning Series (TMLS)

Prompt Optimization and Parameter Efficient Fine Tuning for Large Language Models

Explore state-of-the-art prompt optimization techniques and parameter efficient fine-tuning methods for large language models to enhance performance on various tasks.

• YouTube
• 28 minutes
• On-Demand
• Free Video