Items tagged projects, generativeai in 2023
Filters: Year: 2023 × projects × generativeai × Sorted by date
Many options for running Mistral models in your terminal using LLM
Mistral AI is the most exciting AI research lab at the moment. They’ve now released two extremely powerful smaller Large Language Models under an Apache 2 license, and have a third much larger one that’s available via their API.
[... 2063 words]Exploring GPTs: ChatGPT in a trench coat?
The biggest announcement from last week’s OpenAI DevDay (and there were a LOT of announcements) was GPTs. Users of ChatGPT Plus can now create their own, custom GPT chat bots that other Plus subscribers can then talk to.
[... 5699 words]ospeak: a CLI tool for speaking text in the terminal via OpenAI
I attended OpenAI DevDay today, the first OpenAI developer conference. It was a lot. They released a bewildering array of new API tools, which I’m just beginning to wade my way through fully understanding.
[... 1109 words]Weeknotes: the Datasette Cloud API, a podcast appearance and more
Datasette Cloud now has a documented API, plus a podcast appearance, some LLM plugins work and some geospatial excitement.
[... 1243 words]LLM 0.11. I released LLM 0.11 with support for the new gpt-3.5-turbo-instruct completion model from OpenAI.
The most interesting feature of completion models is the option to request “log probabilities” from them, where each token returned is accompanied by up to 5 alternatives that were considered, along with their scores. # 19th September 2023, 3:28 pm
Build an image search engine with llm-clip, chat with models with llm chat
LLM is my combination CLI tool and Python library for working with Large Language Models. I just released LLM 0.10 with two significant new features: embedding support for binary files and the llm chat command.
Symbex 1.4. New release of my Symbex tool for finding symbols (functions, methods and classes) in a Python codebase. Symbex can now output matching symbols in JSON, CSV or TSV in addition to plain text.
I designed this feature for compatibility with the new “llm embed-multi” command—so you can now use Symbex to find every Python function in a nested directory and then pipe them to LLM to calculate embeddings for every one of them.
I tried it on my projects directory and embedded over 13,000 functions in just a few minutes! Next step is to figure out what kind of interesting things I can do with all of those embeddings. # 5th September 2023, 5:29 pm
LLM now provides tools for working with embeddings
LLM is my Python library and command-line tool for working with language models. I just released LLM 0.9 with a new set of features that extend LLM to provide tools for working with embeddings.
[... 3466 words]llm-mlc (via) My latest plugin for LLM adds support for models that use the MLC Python library—which is the first library I’ve managed to get to run Llama 2 with GPU acceleration on my M2 Mac laptop. # 12th August 2023, 5:33 am
How I make annotated presentations
Giving a talk is a lot of work. I go by a rule of thumb I learned from Damian Conway: a minimum of ten hours of preparation for every one hour spent on stage.
[... 2122 words]Run Llama 2 on your own Mac using LLM and Homebrew
Llama 2 is the latest commercially usable openly licensed Large Language Model, released by Meta AI a few weeks ago. I just released a new plugin for my LLM utility that adds support for Llama 2 and many other llama-cpp compatible models.
[... 1423 words]LLM can now be installed directly from Homebrew (via) I spent a bunch of time on this at the weekend: my LLM tool for interacting with large language models from the terminal has now been accepted into Homebrew core, and can be installed directly using “brew install llm”. I was previously running my own separate tap, but having it in core means that it benefits from Homebrew’s impressive set of build systems—each release of LLM now has Bottles created for it automatically across a range of platforms, so “brew install llm” should quickly download binary assets rather than spending several minutes installing dependencies the slow way. # 24th July 2023, 5:16 pm
Accessing Llama 2 from the command-line with the llm-replicate plugin
The big news today is Llama 2, the new openly licensed Large Language Model from Meta AI. It’s a really big deal:
[... 1206 words]Weeknotes: Self-hosted language models with LLM plugins, a new Datasette tutorial, a dozen package releases, a dozen TILs
A lot of stuff to cover from the past two and a half weeks.
[... 1742 words]My LLM CLI tool now supports self-hosted language models via plugins
LLM is my command-line utility and Python library for working with large language models such as GPT-4. I just released version 0.5 with a huge new feature: you can now install plugins that add support for additional models to the tool, including models that can run on your own hardware.
[... 1656 words]Weeknotes: symbex, LLM prompt templates, a bit of a break
I had a holiday to the UK for a family wedding anniversary and mostly took the time off... except for building symbex, which became one of those projects that kept on inspiring new features.
[... 1120 words]Symbex: search Python code for functions and classes, then pipe them into a LLM
I just released a new Python CLI tool called Symbex. It’s a search tool, loosely inspired by ripgrep, which lets you search Python code for functions and classes by name or wildcard, then see just the source code of those matching entities.
[... 1183 words]LLM 0.4. I released a major update to my LLM CLI tool today—version 0.4, which adds conversation mode and prompt templates so you can store and re-use interesting prompts, plus a whole bunch of other large and small improvements.
I also released 0.4.1 with some minor fixes and the ability to install the tool using Hombrew: brew install simonw/llm/llm # 17th June 2023, 10:58 pm
Understanding GPT tokenizers
Large language models such as GPT-3/4, LLaMA and PaLM work in terms of tokens. They take text, convert it into tokens (integers), then predict which tokens should come next.
[... 1570 words]llm, ttok and strip-tags—CLI tools for working with ChatGPT and other LLMs
I’ve been building out a small suite of command-line tools for working with ChatGPT, GPT-4 and potentially other language models in the future.
[... 1317 words]Enriching data with GPT3.5 and SQLite SQL functions
I shipped openai-to-sqlite 0.3 yesterday with a fun new feature: you can now use the command-line tool to enrich data in a SQLite database by running values through an OpenAI model and saving the results, all in a single SQL query.
[... 1219 words]AI-enhanced development makes me more ambitious with my projects
The thing I’m most excited about in our weird new AI-enhanced reality is the way it allows me to be more ambitious with my projects.
[... 3334 words]Weeknotes: AI won’t slow down, a new newsletter and a huge Datasette refactor
I’m a few weeks behind on my weeknotes, but it’s not through lack of attention to my blog. AI just keeps getting weirder and more interesting.
[... 1255 words]apple-notes-to-sqlite (via) With the help of ChatGPT I finally figured out just enough AppleScript to automate the export of my notes to a SQLite database. AppleScript is a notoriously read-only language, which is turns out makes it a killer app for LLM-assisted coding. # 9th March 2023, 6:04 am
Weeknotes: A bunch of things I learned this week, plus datasette-explain
The Datasette table view refactor, JSON redesign and ?_extra= continues this week, mainly in this ongoing pull request and this tracking issue.
Exploring MusicCaps, the evaluation data released to accompany Google’s MusicLM text-to-music model
Google Research just released MusicLM: Generating Music From Text. It’s a new generative AI model that takes a descriptive prompt and produces a “high-fidelity” music track. Here’s the paper (and a more readable version using arXiv Vanity).
[... 1323 words]How to implement Q&A against your documentation with GPT3, embeddings and Datasette
If you’ve spent any time with GPT-3 or ChatGPT, you’ve likely thought about how useful it would be if you could point them at a specific, current collection of text or documentation and have it use that as part of its input for answering questions.
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