aparente

---

name: tufte-viz description: | Ideate and critique data visualizations using Edward Tufte's principles from "The Visual Display of Quantitative Information." Use this skill when: (1) Designing new data visualizations or charts (2) Critiquing or improving existing visualizations (3) Reviewing dashboards or reports for graphical integrity (4) Deciding between visualization approaches (5) Reducing chartjunk or improving data-ink ratio (6) Planning small multiples or high-density displays

JonnyBurger

                                                                                                                                                            
╭─── Claude Code v2.1.12 ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╮
│                                                     │ Tips for getting started                                                                           │
│                 Welcome back Jonny!                 │ Run /init to create a CLAUDE.md file with instructions for Claude                                  │
│                                                     │                                                                                                    │
│                                                     │ ─────────────────────────────────────────────────────────────────                                  │
│                       ▐▛███▜▌                       │ Recent activity           

OrionReed

// 3D Dom viewer, copy-paste this into your console to visualise the DOM as a stack of solid blocks.
// You can also minify and save it as a bookmarklet (https://www.freecodecamp.org/news/what-are-bookmarklets/)
(() => {
  const SHOW_SIDES = false; // color sides of DOM nodes?
  const COLOR_SURFACE = true; // color tops of DOM nodes?
  const COLOR_RANDOM = false; // randomise color?
  const COLOR_HUE = 190; // hue in HSL (https://hslpicker.com)
  const MAX_ROTATION = 180; // set to 360 to rotate all the way round
  const THICKNESS = 20; // thickness of layers
  const DISTANCE = 10000; // ¯\\_(ツ)_/¯

wilsonowilson

{
  "workbench.colorTheme": "Aura Dark",
  "workbench.iconTheme": "material-icon-theme",
  "editor.fontFamily": "'Geist Mono', Menlo, Monaco, 'Courier New', monospace",
  "apc.listRow": {
    "height": 24,
    "fontSize": 11
  },
  "window.titleBarStyle": "native",
  "apc.font.family": "Geist Mono",

kamilogorek

adrienbrault

# Clone llama.cpp
git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp

# Build it
make clean
LLAMA_METAL=1 make

# Download model
export MODEL=llama-2-13b-chat.ggmlv3.q4_0.bin

josephrocca

// See the comments at the end for a model that does much better than e5-large-v2 while being a third of the size.

let { pipeline } = await import('https://cdn.jsdelivr.net/npm/@xenova/transformers@2.7.0');
let extractor = await pipeline('feature-extraction', 'Xenova/e5-large-v2');

// Note: If you're just comparing "passages" with one another, then just prepend "passage: " to all texts. Only use "query: " if the text is a short "search query" like in the above example.
let passage1 = await extractor(`passage: The Shawshank Redemption is a true masterpiece of cinema.`, { pooling: 'mean', normalize: true });
let passage2 = await extractor(`passage: The film should not be exposed to sunlight when removing it from the wrapper. Otherwise your movie will come out bad.`, { pooling: 'mean', normalize: true });
let query = await extractor(`query: movie review`, { pooling: 'mean', normalize: true });

rain-1

Purpose

Bootstrap knowledge of LLMs ASAP. With a bias/focus to GPT.

Avoid being a link dump. Try to provide only valuable well tuned information.

Prelude

Neural network links before starting with transformers.

Quasimondo

import torch

#USE AT YOUR OWN RISK

#local path to runwayML SD 1.5 checkpoint (https://huggingface.co/runwayml/stable-diffusion-v1-5)
ckpt_15 = "./v1-5-pruned-emaonly.ckpt"

#local path to StabilityAI finetuned autoencoder (https://huggingface.co/stabilityai/sd-vae-ft-mse)
ckpt_vae = "./vae-ft-mse-840000-ema-pruned.ckpt"

veqtor

# This is a sample Python script.

# Press ⌃R to execute it or replace it with your code.
# Press Double ⇧ to search everywhere for classes, files, tool windows, actions, and settings.

import aiohttp

event_loop = None
import asyncio
from pprint import pprint