Published on: 2025-06-07 15:25:54
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: 2025-06-23 17:00:15
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: 2025-06-28 21:23:05
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: 2025-07-03 03:41:14
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: 2025-07-06 23:38:50
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: 2025-07-11 23:57:13
[ 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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