Foundation Models Tutorial and Why Not to Fine-Tune Them
Explore Foundation Models: capabilities, adaptation, risks. Learn why fine-tuning can distort pre-trained features and underperform. Gain insights into responsible AI development and interdisciplinary research approaches.
Data Labeling Best Practices for Fine-Tuning LLMs
Discover best practices for data labeling in LLM fine-tuning. Learn strategies for hiring, data preparation, and managing labelers to enhance AI model performance.
Fine-tuning Large Models on Local Hardware Using PEFT and Quantization
Explore Parameter-Efficient Fine-Tuning (PEFT) and quantization techniques to train large neural networks on modest hardware using the PEFT library and Hugging Face ecosystem.
Representation is King: The Journey to Quality Dialog Embeddings
Explore sentence embeddings in dialog systems, focusing on classification. Learn to fine-tune top-performing small-sized sentence transformers using SentenceTransformers framework with practical examples.
Abacus ChatLLM - Creating and Deploying Custom Chatbots with RAG
Create and deploy custom chatbots with Abacus AI's Chat LLM interface. Learn data management, RAG setup, fine-tuning, and integration for powerful, cost-effective AI solutions.
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.
RAG vs PEFT - Comparing LLM Domain Adaptation Methods
Delve into LLM 도메인 적용을 위한 RAG와 PEFT 방식의 비교 분석과 SK브로드밴드의 실제 구현 사례를 통한 AWS 환경 구축 및 모델 개발 노하우
SKT LLM Enterprise 서비스 - 기업용 맞춤형 LLM 최적화 솔루션
Discover SKT의 맞춤형 LLM Enterprise 서비스 개발 과정과 기술적 접근 방식을 통해 기업 환경에 최적화된 AI 솔루션 구현 방법을 탐구하는 기술 세션
Understanding Robotics Transformer 2 (RT-2) - A Deep Dive into DeepMind's Vision-Language-Action Model
Explore DeepMind's RT2 model and discover how it bridges language models with robotics to enable intelligent reasoning and action in autonomous systems.
Make LLM Apps Sane Again - Forgetting Incorrect Data in Real Time
Explore real-time data correction in LLM applications using vector indexing. Learn to build a chatbot that adapts to changing information, ensuring accuracy and reliability in AI-powered conversations.
Data Curation for Open Source LLM Fine-Tuning
Explore data curation challenges and strategies for fine-tuning open source LLMs, focusing on dataset quality and iteration techniques for improved results.
PockEngine: Sparse and Efficient Fine-tuning in a Pocket
Explore sparse and efficient fine-tuning techniques for AI models with PockEngine, enhancing performance while reducing computational demands.
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.
When, Why and How to Fine-Tune LLMs for Enterprise Applications
Explore techniques for customizing large language models in enterprise settings, including when and why to align LLMs and key methods for domain-specific adaptation.
Fine-Tuning and Customizing LLMs for Enterprise Tasks
Explore LLM fine-tuning techniques for enterprise-specific tasks. Learn about data quality, customization methods, and the trend towards task-specific models in organizational AI implementation.
Scaling Language Model Tuning with Snorkel AI - A Case Study
Explore Snorkel AI's innovative approach to scaling language model tuning using programmatic labeling and guiding models for efficient data curation and improved performance.
Digging Into RAG and the Future of AI - With Douwe Keila
Explore RAG applications, AI's enterprise future, and the role of data in improving AI systems with industry experts Alex Ratner and Douwe Keila.
Best Practices and Tips for Fine-Tuning Representation Models
Discover techniques to enhance generative applications through representation model fine-tuning. Learn data quality strategies, augmentation methods, and optimization tips for RAG-based pipelines.
Securing GenAI End-to-End: From Development to Deployment
Explore comprehensive strategies for securing AI-powered applications throughout the software supply chain, from data ingestion to model deployment and output protection.
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.
Create a Contextual Chatbot with LLM and Vector Database in 10 Minutes
Learn to build a contextual chatbot using LLM and vector database, exploring embedding, search, and answer generation with Langchain.