Published on: 2025-07-06 10:06:02
Writing an LLM from scratch, part 13 -- the 'why' of attention, or: attention heads are dumb Now that I've finished chapter 3 of Sebastian Raschka's book "Build a Large Language Model (from Scratch)" -- having worked my way through multi-head attention in the last post -- I thought it would be worth pausing to take stock before moving on to Chapter 4. There are two things I want to cover, the "why" of self-attention, and some thoughts on context lengths. This post is on the "why" -- that is, w
Keywords: attention embedding head input space
Find related items on AmazonPublished on: 2025-07-16 17:01:57
Continue is seeking an outstanding software engineer to help us build state-of-the-art autocomplete and codebase retrieval, who thinks rigorously and pays attention to the smallest details. In this role, you will work on fundamental, but highly open-ended problems where deliberate measurement, rapid experimentation, and empathy for users push forward the product. About you Please keep in mind that we are describing the background that we imagine would best fit the role. If you don’t meet all t
Keywords: absolutely attention highly js role
Find related items on AmazonPublished on: 2025-07-18 23:30:00
Attention to Detail F1 superfan and Lego community ambassador Nicole, who goes by the name GirlBricksALot, concurs. “Down to the spoons for the side-view mirrors, the tiles that are used for the camera mount on top, even the cheese slope piece on the front wing—they’re identical,” she says. “Every part of the car is satisfying.” This isn't Lego's first Big Build in this space. In 2018, its designers brought that same commitment to authenticity with the drivable 1:1 Lego Bugatti made from Lego
Keywords: attention build course f1 lego
Find related items on AmazonPublished on: 2025-07-20 15:30:00
Attention to Detail F1 superfan and Lego ambassador Nicole, who goes by the name GirlBricksALot, concurs. “Down to the spoons for the side view mirrors, the tiles that are used for the camera mount on top, even the cheese slope piece on the front wing—they’re identical,” she says. “Every part of the car is satisfying.” This isn't Lego's first Big Build in this space. In 2018, its designers brought that same commitment to authenticity with the drivable 1:1 Lego Bugatti made from Lego Technic el
Keywords: attention build course driver lego
Find related items on AmazonPublished on: 2025-07-18 06:53:46
On the speed of ViTs and CNNs You disabled JavaScript. Please enable it for syntax-highlighting, or don't complain about unlegible code snippets =) This page doesn't contain any tracking/analytics/ad code. Context Computer vision is now powered by two workhorse architectures: Convolutional Neural Networks (CNN) and Vision Transformers (ViT). CNNs slide a feature extractor (stack of convolutions) over the image to get the final, usually lower-resolution, feature map on which the task is perfor
Keywords: attention image resolution vit vits
Find related items on AmazonPublished on: 2025-07-29 16:47:04
Implement Flash Attention Backend in SGLang - Basics and KV Cache April 26, 2025 Authored by Biao He Qingquan Song 0x0. Introduction In the past few weeks, we’ve implemented the Flash Attention Backend end-to-end in SGLang, which is now the default attention backend as of SGLang 0.4.6 release. Throughout this journey, we learned a lot about how Attention Backend functions in modern LLM serving engines and developed a deeper understanding of Flash Attention itself. In this series, we’ll walk
Keywords: attention backend kv metadata torch
Find related items on AmazonPublished on: 2025-07-31 10:24:41
tiny-llm - LLM Serving in a Week Still WIP and in very early stage. A tutorial on LLM serving using MLX for system engineers. The codebase is solely (almost!) based on MLX array/matrix APIs without any high-level neural network APIs, so that we can build the model serving infrastructure from scratch and dig into the optimizations. The goal is to learn the techniques behind efficiently serving an LLM model (i.e., Qwen2 models). Book The tiny-llm book is available at https://skyzh.github.io/ti
Keywords: attention llm model serving tiny
Find related items on AmazonPublished on: 2025-07-31 16:41:37
She’s an exceptionally bright student. I’d taught her before, and I knew her to be quick and diligent. So what, exactly, did she mean? She wasn’t sure, really. It had to do with the fact that the machine . . . wasn’t a person. And that meant she didn’t feel responsible for it in any way. And that, she said, felt . . . profoundly liberating. We sat in silence. She had said what she meant, and I was slowly seeing into her insight. Like more young women than young men, she paid close attention
Keywords: attention human said systems work
Find related items on AmazonPublished on: 2025-07-31 21:08:14
Shit's gotten weird out there. The internet has devolved from something that was mostly quirky and altruistic to something that, in many ways, is straight-up evil. Companies have commoditized user attention through an economic framework that is completely divorced from the user's experience: Advertisers go to some ad platform, set up a few tags, and third parties shill for them without knowing anything about advertiser or user. The user's experience is determined by some algorithm whose sole pur
Keywords: attention reader rss user using
Find related items on AmazonPublished on: 2025-08-09 08:41:02
Graphs are everywhere. From modeling molecular interactions and social networks to detecting financial fraud, learning from graph data is powerful—but inherently challenging. While Graph Neural Networks (GNNs) have opened up new possibilities by capturing local neighborhood patterns, they face limitations in handling complex, long-range relationships across the graph. Enter Graph Transformers, a new class of models designed to elegantly overcome these limitations through powerful self-attention
Keywords: attention graph node nodes transformers
Find related items on AmazonPublished on: 2025-10-01 01:25:54
Writing an LLM from scratch, part 10 -- dropout I'm still chugging through chapter 3 of Sebastian Raschka's "Build a Large Language Model (from Scratch)". Last time I covered causal attention, which was pretty simple when it came down to it. Today it's another quick and easy one -- dropout. The concept is pretty simple: you want knowledge to be spread broadly across your model, not concentrated in a few places. Doing that means that all of your parameters are pulling their weight, and you don'
Keywords: 0000 attention dropout sat weights
Find related items on AmazonPublished on: 2025-10-17 03:00:15
One night shortly before the Oscars ceremony, my boyfriend decided to catch up on “Flow,” the animated film from Latvia that would go on to win best animated feature. When I returned home from dinner, I found that the film had also captured the attention of another viewer — my dog Daisy, a corgi mix. Search on TikTok and you’ll find a number of videos of dogs and cats alike viewing “Flow” alongside their owners, appearing to recognize themselves in the gentle saga, which tells the tale of an ad
Keywords: animated attention flow home means
Find related items on AmazonPublished on: 2025-10-22 07:23:05
Hello, passionate learners from around the world ✌️ In 2023 ChatGPT from OpenAI reached 100 million users faster than other solutions in Web 2.0 era. Source: Yahoo Finance And since then many intelligent models from Anthropic, Cohere, IBM, Goole, Amazon, Meta AI, DeepSeek, HuggingFace come up and also many startups entering the arena. It’s interesting times to invest in our skillset. Platforms like HuggingFace—the GitHub of AI—serving as open hubs where an entire ecosystem of researchers and
Keywords: attention embedding model models token
Find related items on AmazonPublished on: 2025-10-26 13:41:14
Writing an LLM from scratch, part 8 -- trainable self-attention This is the eighth post in my trek through Sebastian Raschka's book "Build a Large Language Model (from Scratch)". I'm blogging about bits that grab my interest, and things I had to rack my brains over, as a way to get things straight in my own head -- and perhaps to help anyone else that is working through it too. It's been almost a month since my last update -- and if you were suspecting that I was blogging about blogging and spe
Keywords: attention input matrix space token
Find related items on AmazonPublished on: 2025-10-30 09:38:50
From the Frontier Research Team at takara.ai we present the first pure Go implementation of attention mechanisms and transformer layers, designed for high performance and ease of use. Quick Start Run our comprehensive examples: # Get the module go get github.com/takara-ai/go-attention # Run the examples go run api_examples.go API Documentation Core Types type Vector [] float64 // Represents a 1D vector of float64 values type Matrix [] Vector // Represents a 2D matrix of float64 values 1.
Keywords: attention err input layer transformer
Find related items on AmazonPublished on: 2025-11-04 20:57:13
[ View in English | 中文版文档点这里 ] This project is an enhanced version based on naklecha/llama3-from-scratch. It has been comprehensively improved and optimized on the basis of the original project, aiming to help everyone more easily understand and master the implementation principle and the detailed reasoning process of the Llama3 model. Thanks to the contributions of the original author :) The following are the core improvements of this project: Structural Optimization The presentation se
Keywords: attention inf token tokens torch
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