TLDR; Maybe. Longer answer: Capitalism sucks, hard. It’s the bad card we’ve been dealt, for-profit companies will always be looking to reduce costs and increase profits. If this means they can reduce expenses by automating an activity - they will (eventually). To look at this another way - if the output of your job is repeatable and not creative - one could argue that (other than providing you income), it might also not be the best use of your time. ...
The two tools I use with AI / LLMs for generating diagrams are Mermaid and Excalidraw. Mermaid (or MermaidJS) is a popular diagramming library and format supported by many tools and is often rendered inside markdown (e.g. in a readme.md). Excalidraw is an excellent, free and open source diagramming and visualisation tool. I also often make use of a third party Obsidian plugin for Excalidraw. Excalidraw It has a ‘generate diagram with AI’ feature which if you’re using the excalidraw.com online editor offers a few free generations each day (I think this uses a low-end OpenAI model). If you’re running Excalidraw locally or by using the brilliant Obsidian plugin - you can provide any OpenAI compatible API endpoint and model for AI generations. Behind the scenes Excalidraw AI generates and then renders MermaidJS. ...
Ingest is a tool I’ve written to make my life easier when preparing content for LLMs. It parses directories of plain text files, such as source code, documentation etc… into a single markdown file suitable for ingestion by AI/LLMs. Ingest can also estimate vRAM requirements for a given model, quantisation and context length: Features Traverse directory structures and generate a tree view Include/exclude files based on glob patterns Estimate vRAM requirements and check model compatibility using another package I’ve created called quantest Parse output directly to LLMs such as Ollama or any OpenAI compatible API for processing Generate and include git diffs and logs Count approximate tokens for LLM compatibility Customisable output templates Copy output to clipboard (when available) Export to file or print to console Optional JSON output Ingest Intro (“Podcast” Episode): ...
Here’s a fun little tool I’ve been hacking on to explore the effects of different inference parameters on LLMs. You can find the code and instructions for running it locally on GitHub. It started as a fork of rooben-me’s tone-changer-open, which itself was a “fork” of Figma’s tone generator, I’ve made quite a few changes to make it more focused on local LLMs and advanced parameter exploration.
Code, Chaos, and Copilots is a talk I gave in July 2024 as an intro to how I use AI/LLMs to augment my capabilities every day. What I use AI/LLMs for Prompting tips Codegen workflow Picking the right models Model formats Context windows Quantisation Model servers Inference parameters Clients & tools Getting started cheat-sheets Download Slide Deck Disclaimer I’m not a ML Engineer or data scientist, As such, the information presented here is based on my understanding of the subject and may not be 100% accurate or complete. ...
SuperPrompter is a Python-based application that utilises the SuperPrompt-v1 model to generate optimised text prompts for AI/LLM image generation (for use with Stable Diffusion etc…) from user prompts. See Brian Fitzgerald’s Blog for a detailed explanation of the SuperPrompt-v1 model and its capabilities / limitations. Features Utilises the SuperPrompt-v1 model for text generation. A basic (aka ugly) graphical user interface built with tkinter. Customisable generation parameters (max new tokens, repetition penalty, temperature, top p, top k, seed). Optional logging of input parameters and generated outputs. Bundling options to include or exclude pre-downloaded model files. Unloads the models when the application is idle to free up memory. Prebuilt Binaries Check releases page to see if there are any prebuilt binaries available for your platform. ...
Two of my most commonly used LLM tools are Ollama and LM Studio. Unfortunately they store their models in different locations and filenames. Manually copying or linking files was a pain, so I wrote a simple command-line tool to automate the process. This is why I created Llamalink. Ollama is a cross-platform model server that allows you to run LLMs and manage their models in a similar way to Docker containers and images, while LM Studio is a macOS app that provides a user-friendly interface for running LLMs. ...
Offline AI / LLM Assistant More info on this soon but the basic idea was to use Willow, Home Assistant and local LLM models to create a locally hosted, offline, AI powered Siri replacement and interface it with ESP32 S3 Box 3 devices. ...
“MBA Washing” refers to the phenomenon where individuals, often with a strong theoretical or academic background but limited recent practical experience, adopt and reinterpret industry-specific terminology and cultural movements. – This reinterpretation is typically influenced by their academic learning, recent literature, and biases towards larger enterprise perspectives. As a result, the original intent and practical effectiveness of these concepts, such as DevOps or Platform Engineering for example, may be diluted or misrepresented. ...
A talk I gave to some peers on creating your own SDXL LoRA models from my tinkering around over the last few weeks. ...