AI, Quant 투자 공부

An Intuition for Attention An Intuition for Attention | Jay Mody Deriving the equation for scaled dot product attention. jaykmody.com De-coded: Transformers explained in plain English De-coded: Transformers explained in plain English No code, maths, or mention of Keys, Queries and Values towardsdatascience.com

Efficient Streaming Language Models with Attention Sinks Efficient Streaming Language Models with Attention Sinks Deploying Large Language Models (LLMs) in streaming applications such as multi-round dialogue, where long interactions are expected, is urgently needed but poses two major challenges. Firstly, during the decoding stage, caching previous tokens' Key and Val arxiv.org Ring Attention wi..

Add Your Own Data to an LLM Using Retrieval-Augmented Generation (RAG) Add Your Own Data to an LLM Using Retrieval-Augmented Generation (RAG) Learn how to add your own proprietary data to a pre-trained LLM using a prompt-based technique called Retrieval-Augmented Generation. towardsdatascience.com RAG vs Finetuning — Which Is the Best Tool to Boost Your LLM Application? RAG vs Finetuning — Which..

Making Deep Learning Go Brrrr From First Principles

7 Ways To Speed Up Inference of Your Hosted LLMs 7 Ways to Speed Up Inference of Your Hosted LLMs TLDR; techniques to speed up inference of LLMs to increase token generation speed and reduce memory consumption betterprogramming.pub Fixing Hallucinations in LLMs

From Sparse to Dense: GPT-4 Summarization with Chain of Density Prompting NExT-GPT: Any-to-Any Multimodal LLM When Less is More: Investigating Data Pruning for Pretraining LLMs at Scale GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints Optimizing your LLM in production Do Machine Learning Models Memorize or Generalize? Do Machine Learning Models Memorize or Gen..

Language Modeling Is Compression Building RAG-based LLM Applications for Production (Part 1) Building RAG-based LLM Applications for Production (Part 1) In this guide, we will learn how to develop and productionize a retrieval augmented generation (RAG) based LLM application, with a focus on scale, evaluation and routing. www.anyscale.com 10 Ways to Improve the Performance of Retrieval Augmented..

Textbooks Are All You Need Textbooks Are All You Need II: phi-1.5 technical report Draft & Verify: Lossless Large Language Model Acceleration via Self-Speculative Decoding

The Economics of Large Language Models

Full Stack Optimization of Transformer Inference: a Survey How long Can Open-Source LLMs Truly Promise on Context Length? How Long Can Open-Source LLMs Truly Promise on Context Length? | LMSYS Org In this blogpost, we introduce our latest series of chatbot models, LongChat-7B and LongChat-13B, featuring a new level of extended context length up to 1... lmsys.org EFFICIENTLY SCALING TRANSFORMER I..