Author: Jeod
Contributors:
- TerrorTowers
- hxdr0n0s
- Unstoppable
- Agent
// 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)_/¯ |
I want this paper and exercise to be fun and enlightening for everyone.
I will try to make it fun and easy to follow along without glossing over too much of the underlying maths.
That being said, if this is not for you, or you just hate math, I encourage you to still try.
I will be adding python code blocks you can run as we move through the paper which I hope will make it more interactive and engaging.
#!/usr/bin/env sh | |
URI=$1 | |
BASE=$(basename $1) | |
[ -f ../models/$BASE-f16.gguf ] && exit 0 | |
(. ../huggingface-cli/bin/activate && HF_HUB_ENABLE_HF_TRANSFER=1 huggingface-cli download $URI --local-dir ../models/$BASE --cache-dir ../models/$BASE/.hf-cache --exclude 'pytorch_model*' --exclude 'consolidated*' --resume-download) || exit 1 | |
DTYPE=$(jq -r '.torch_dtype' < ../models/$BASE/config.json) |
Good question! I am collecting human data on how quantization affects outputs. See here for more information: ggerganov/llama.cpp#5962
In the meantime, use the largest that fully fits in your GPU. If you can comfortably fit Q4_K_S, try using a model with more parameters.
See the wiki upstream: https://github.com/ggerganov/llama.cpp/wiki/Feature-matrix
In addition to a significant decrease in hepatic lipid accumulation in the IOE group, which inhibited energy intake by propionate enrichment, hepatic lipids were also significantly reduced in the mice in the IOP group, which was largely enriched with butyrate. Compared with the IOE group, IOP had a stronger regulatory effect on hepatic metabolism and triglyceride metabolism and higher levels of TCA cycle in the host. In addition, butyrate has the ability to promote browning of white adipose tissue (WAT) to brown adipose tissue (BAT).^[@ref39],[@ref40]^ WAT stores energy, whereas BAT uses energy for heating and consequently host energy expenditure increases.^[@ref41],[@ref42]^ However, adipose tissue weight does not change after WAT browning.^[@ref43]^ Therefore, the weight of adipose tissue of mice in the IOP group dominated by butyrate was greater than that of the mice in the IOE group dominated by propionate. | |
In conclusion ([Figure [7](#fig7){ref-type="fig"}](#fig7){ref-type="fig"}C), the improvement of ob |
I hereby claim:
To claim this, I am signing this object:
Mini projects by Maxime Euzière (xem), subzey, Martin Kleppe (aemkei), Mathieu Henri (p01), Litterallylara, Tommy Hodgins (innovati), Veu(beke), Anders Kaare, Keith Clark, Addy Osmani, bburky, rlauck, cmoreau, maettig, thiemowmde, ilesinge, adlq, solinca, xen_the,...
(For more info and other projects, visit http://xem.github.io)
(Official Slack room: http://jsgolf.club / join us on http://register.jsgolf.club)
________ ___ _ ______ _____ ____ ____ _____ _ _ _____ _______ _ _
| ____\ \ / / | | | ____| __ \| _ \ / __ \ |_ _| \ | |/ ____|__ __|/\ | | | |
| |__ \ V /| |__| | |__ | |__) | |_) | | | |______| | | \| | (___ | | / \ | | | |
| __| > < | __ | __| | _ /| _ <| | | |______| | | . ` |\___ \ | | / /\ \ | | | |
| |____ / . \| | | | |____| | \ \| |_) | |__| | _| |_| |\ |____) | | |/ ____ \| |____| |____
|______/_/ \_\_| |_|______|_| \_\____/ \____/ |_____|_| \_|_____/ |_/_/ \_\______|______|
This guide is based on several documentations