Brunobkr/llama.cpp_AlgMor24_github
ΩFFFΣLLIa • llama.cpp • AlgMor24 ██████╗ ███████╗███████╗███████╗██╗ ██╗ ██╗ █████╗ ██╔═══██╗██╔════╝██╔════╝██╔════╝██║ ██║ ██║██╔══██╗ ██║ ██║█████╗ █████╗ █████╗ ██║ ██║ ██║███████║ ██║ ██║██╔══╝ ██╔══╝ ██╔══╝ ██║ ██║ ██║██╔══██║ ╚██████╔╝██║ ██║ ███████╗███████╗███████╗██║██║ ██║ ╚═════╝ ╚═╝ ╚═╝ ╚══════╝╚══════╝╚══════╝╚═╝╚═╝ ╚═╝ High-Performance LLM / VLM Inference & Autonomous Agentic Ecosystem… See the full description on the dataset page: https://huggingface.co/datasets/Brunobkr/llama.cpp_AlgMor24_github.
03k
1import {bisect} from "d3-array";2import {linearish} from "./linear.js";3import {initRange} from "./init.js";4 5export default function quantize() {6 var x0 = 0,7 x1 = 1,8 n = 1,9 domain = [0.5],10 range = [0, 1],11 unknown;12 13 function scale(x) {14 return x != null && x <= x ? range[bisect(domain, x, 0, n)] : unknown;15 }16 17 function rescale() {18 var i = -1;19 domain = new Array(n);20 while (++i < n) domain[i] = ((i + 1) * x1 - (i - n) * x0) / (n + 1);21 return scale;22 }23 24 scale.domain = function(_) {25 return arguments.length ? ([x0, x1] = _, x0 = +x0, x1 = +x1, rescale()) : [x0, x1];26 };27 28 scale.range = function(_) {29 return arguments.length ? (n = (range = Array.from(_)).length - 1, rescale()) : range.slice();30 };31 32 scale.invertExtent = function(y) {33 var i = range.indexOf(y);34 return i < 0 ? [NaN, NaN]35 : i < 1 ? [x0, domain[0]]36 : i >= n ? [domain[n - 1], x1]37 : [domain[i - 1], domain[i]];38 };39 40 scale.unknown = function(_) {41 return arguments.length ? (unknown = _, scale) : scale;42 };43 44 scale.thresholds = function() {45 return domain.slice();46 };47 48 scale.copy = function() {49 return quantize()50 .domain([x0, x1])51 .range(range)52 .unknown(unknown);53 };54 55 return initRange.apply(linearish(scale), arguments);56}57 