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// 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)_/¯ |
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{ | |
"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", |
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# 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 |
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// 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 }); |
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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" |
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# 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 |
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// add script to a button inside Cryptovoxels to return a response | |
feature.on('click',e=>{ | |
// Use GraphQL endpoint to pull data and make model that takes x,y Decentraland coordinates and returns prediction based on the latest 10 sales! | |
fetch('https://api.thegraph.com/subgraphs/name/decentraland/marketplace', { | |
method: 'POST', | |
headers: { | |
'Content-Type': 'application/json', |
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query findSecondarySales($address: String = "tz1c2iwyckUCcicx2qxqtwLEartYFEHg1pvB") { | |
hic_et_nunc_swap(where: {status: {_in: [1]}, token: {swaps: {trades: {buyer: {address: {_eq: $address}}}}}}, order_by: {price: desc}) { | |
price | |
status | |
token { | |
title | |
mime | |
description | |
id | |
artifact_uri |
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