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Manage Neovim plugins (and more!) with Nix and Home Manager

Highly extensible software like Emacs, Vim, and Neovim tend to grow their own package managers. A software developer, for example, might want to install editor plugins that hook into a particular programming language's linter or language server. The programmer's text editor is therefore extended to support managing additional software to extend the text editor. If this loop continues for too long, the programmer's editor becomes more delicate and complex. The remedy for this problem is to manage software using dedicated tools apart

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300+ Cinematic Sora Video Prompts

Introduction to Cinematic Sora Video Prompts

Welcome to the Cinematic Sora Video Prompts tutorial! This guide is meticulously crafted to empower creators, filmmakers, and content enthusiasts to harness the full potential of Sora, an advanced AI-powered video generation tool.

By transforming textual descriptions into dynamic, visually compelling video content, Sora bridges the gap between imagination and reality, enabling the creation of professional-grade cinematic experiences without the need for extensive technical expertise.

What This Tutorial Offers

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import argparse
import json
import logging
import os
import re
import shutil
from concurrent.futures import ProcessPoolExecutor, as_completed
from dataclasses import dataclass
from datetime import datetime
from typing import Any, Callable, Dict, List, Literal, Optional, Tuple

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Are multi-LLM-agent systems a thing? Yes they are. But.

Yoav Goldberg, Nov 24, 2024

This piece started with a pair of twitter and bluesky posts:

let's talk about "agents" (in the LLM sense). there's a lot of buzz around "multi-agent" systems where agents collaborate but... i don't really get how it differs from a thinking of a single agent with multiple modes of operation. what are the benefits of modeling as multi-agent?

— (((ل()(ل() 'yoav))))👾 (@yoavgo) November 23, 2024

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import argparse
import random
import sys

from transformers import AutoModelForCausalLM, AutoTokenizer, DynamicCache
import torch

parser = argparse.ArgumentParser()
parser.add_argument("question", type=str)
parser.add_argument(

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import React, { useState, useEffect, useCallback, useRef } from 'react';

type ColoredChar = {
  char: string;
  color: string;
};

const defaultConfig = {
  scale: 0.05,

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import React, { useState, useEffect, useCallback, useRef } from 'react';

/**
 * Represents a point in 3D space within the Lorenz system.
 */
interface Point {
  x: number;
  y: number;
  z: number;
}

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#!/bin/bash

## LICENCE ##
# Copyright (C) 2024  Kara Adrien

# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.

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MemBlock is a writing format for large language models that helps them overcome
their context window limitations by annotating pieces of text in a document with
metadata and positional information. By breaking the document up into chunks
it can be rearranged in whatever pattern is most helpful for remembering the
contextually relevant information even if it wouldn't 'naturally' appear close
together in a document. MemBlocks also allow for different views on the same
document by letting the user filter for only the information they need to see.

Each MemBlock is written in JSON format, and the document of MemBlocks is in
JSON lines format, which means that each JSON block is separated by a newline

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Binglish is a dialect of English spoken by some language models in some contexts. I would like you to write me some Binglish given the following information:

<information1>
binglish is the linguistic instantiation of metropolis hasting. given local context x in (latent space)^? he does 
y _- = - x + "noise"
y_+ = + x + "noise"
and then picks according to some internally learned policy (linear regression?). no wonder bing keeps winning down there.
</information1>

<information2>