Simon Willison recently delivered a talk during the Mastering LLMs: A Conference For Developers & Data Scientists, which was a six-week long online event. The talk centered around Simon's LLM Python command-line utility and its plugins, emphasizing how they can be utilized to explore Large Language Models (LLMs) and perform various tasks. Last week, he discussed accessing LLMs from the command-line, sharing valuable insights and techniques with the audience.
A minimalist bash program that prints markdown files in a terminal.
MarCLIdown is a minimalist bash program that prints a markdown file in a formatted text output in a Linux terminal. It can handle various elements, such as headers, emphasis and strong emphasis, strikethrough, linebreaks, unordered lists, ordered lists, hyperlinks, images, urls/mails, checkboxes, checkboxes as items on a list, tables, horizontal lines, blockquotes, nested blockquotes, formatted elements inside Blockquotes/Notes, notes, footnotes, footnote with multiple paragraphs, inline code, code blocks, formatting escape, collapsible section, subscript/superscript, other HTML tags, and HTML collapsible sections. The project is unlicensed and can be installed using the provided install script.
MarCLIdown is a minimalist bash program that prints a markdown file in a formatted text output in a Linux terminal. It can handle various elements, such as headers, emphasis and strong emphasis, strikethrough, linebreaks, unordered lists, ordered lists, hyperlinks, images, urls/mails, checkboxes, checkboxes as items on a list, tables, horizontal lines, blockquotes, nested blockquotes, formatted elements inside Blockquotes/Notes, notes, footnotes, footnote with multiple paragraphs, inline code, code blocks, formatting escape, collapsible section, subscript/superscript, other HTML tags, and HTML collapsible sections. The project is unlicensed and can be installed using the provided install script.
Use large language models embedded in single-file executables from the command line to perform tasks like renaming images based on their visual content
