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Bridgy Fed
Core documentation for Fediverse bridging (bluesky, web, etc)
QED and QCD - the basics
Run an LLM Locally with LM Studio - KDnuggets
Document about LM Studio
Optimum
Optimum is an extension of Transformers that provides a set of performance optimization tools to train and run models on targeted hardware with maximum efficiency. It is also the repository of small, mini, tiny models.
LM Studio on Discord
BERT Transformers – How Do They Work? | Exxact Blog
Excellent document about BERT transformers / models and their parameters: - L=number of layers. - H=size of the hidden layer = number of vectors for each word in the sentence. - A = Number of self-attention heads - Total parameters.
Generative pre-trained transformer - Wikipedia
AMD Ryzen AI CPUs & Radeon 7000 GPUs Can Run Localized Chatbots Using LLMs Just Like NVIDIA's Chat With RTX
LM Studio can be installed on Linux with APU or GPU (looks like it needs the AI CPU though??) and run LLM. Install on Laptop and test if it works.
What is Epoch in Machine Learning?| UNext | UNext
Training and Validation Loss in Deep Learning | Baeldung on Computer Science
A Step-by-Step Guide to Model Evaluation in Python | by Shreya Singh | Medium
ROCm installation for Linux — ROCm installation (Linux)
Top of the guide describing ROCm on Linux. There are 2 core approaches: Using RPM (Package manager), or using AMD installer. I should use Package manager. Also single-version vs. multi-version. I should use single-version, latest.
(1) Most cost effective GPU for local LLMs? : LocalLLaMA
GGML quantized models. They would let you leverage CPU and system RAM, instead of having to rely on a GPU’s. This could save you a fortune, especially if go for some used AMD Epyc platforms. This could be more viable for the larger models, especially the 30B/65B parameters models which would still press or exceed the VRAM on the P40.
Optimizing LLMs for Speed and Memory
7 Steps to Mastering Large Language Models (LLMs) - KDnuggets
A Step-by-Step Guide to Training Your Own Large Language Models (LLMs). | by Sanjay Singh | GoPenAI
GenAI Stack Exchange
7 steps to master large language models (LLMs) | Data Science Dojo
Up to date List of LLM Models
Large Language Models for Domain-Specific Language Generation: How to Train Your Dragon | by Andreas Mülder | Medium
training a model like Llama with 2.7 billion parameters outperformed a larger model like Vicuna with 13 billion parameters. Especially when considering resource consumption, this might be a good alternative to using a 7B Foundation model instead of a full-blown ChatGPT. The best price-to-performance base model for our use case turned out to be Mistral 7b. The model is compact enough to fit into an affordable GPU with 24GB VRAM and outperforms the other models with 7B parameters.
Yelp Review Classification. Using Embedding, CNN and LSTM | by Zhiwei Zhang | Medium
Simpliest start with ai. Use the Github code linked in
Replit — How to train your own Large Language Models
Hi level only talk about training for a language
How to train a new language model from scratch using Transformers and Tokenizers
Describes how to train a new language (desperanto) model.
Web technology for developers | MDN
Learn PWA | web.dev
Markdown Guide
pure-sh-bible: A collection of pure POSIX sh alternatives to external processes.
bash-style-guide
QuickRef.ME - Quick Reference Cheat Sheet
HTML: HyperText Markup Language | MDN
Systemd Unit Configuration Files Explained
Want, WantedBy, Before, After etc -
Tour of the Wasm Ecosystem
What is the difference between asm.js and WebAssembly? (javascript) - StackForGeeks
WebAssembly | MDN
WebAssembly
About Emscripten — Emscripten 3.1.49-git (dev) documentation
Emscripten is a complete Open Source compiler toolchain to WebAssembly. Using Emscripten you can: Compile C and C++ code, or any other language that uses LLVM, into WebAssembly, and run it on the Web, Node.js, or other Wasm runtimes.
Introduction to reactive systems - IBM Developer
Man page of systemd.unit
Main man/doc page of systemctl
bbatsov/emacs-lisp-style-guide: A community-driven Emacs Lisp style guide
ActivityPub
Home :: Sacha Chua
fediverse.info | The bespoke fediverse guide.
Eshell: The Emacs Shell
A Complete Guide on How To Use Bash Arrays
Good guide and doc for Bash arrays. Also clearly states difference between array (indexed array=list) and associative array (keyd array=map)
Org-Babel Cheat Sheet
Great summary of org-babel especially all the tricky header variables.
Foundation - Material Design
Core site for Material design documentation
flutter/packages/integration_test at master · flutter/flutter
Example of testing a Flutter app.