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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.

sourceHugging Faceupdated 2mo agoView on Hugging Face
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linear.js71 linesDownload Raw Back to src
1import {ticks, tickIncrement} from "d3-array";2import continuous, {copy} from "./continuous.js";3import {initRange} from "./init.js";4import tickFormat from "./tickFormat.js";5 6export function linearish(scale) {7  var domain = scale.domain;8 9  scale.ticks = function(count) {10    var d = domain();11    return ticks(d[0], d[d.length - 1], count == null ? 10 : count);12  };13 14  scale.tickFormat = function(count, specifier) {15    var d = domain();16    return tickFormat(d[0], d[d.length - 1], count == null ? 10 : count, specifier);17  };18 19  scale.nice = function(count) {20    if (count == null) count = 10;21 22    var d = domain();23    var i0 = 0;24    var i1 = d.length - 1;25    var start = d[i0];26    var stop = d[i1];27    var prestep;28    var step;29    var maxIter = 10;30 31    if (stop < start) {32      step = start, start = stop, stop = step;33      step = i0, i0 = i1, i1 = step;34    }35    36    while (maxIter-- > 0) {37      step = tickIncrement(start, stop, count);38      if (step === prestep) {39        d[i0] = start40        d[i1] = stop41        return domain(d);42      } else if (step > 0) {43        start = Math.floor(start / step) * step;44        stop = Math.ceil(stop / step) * step;45      } else if (step < 0) {46        start = Math.ceil(start * step) / step;47        stop = Math.floor(stop * step) / step;48      } else {49        break;50      }51      prestep = step;52    }53 54    return scale;55  };56 57  return scale;58}59 60export default function linear() {61  var scale = continuous();62 63  scale.copy = function() {64    return copy(scale, linear());65  };66 67  initRange.apply(scale, arguments);68 69  return linearish(scale);70}71 
Brunobkr/llama.cpp_AlgMor24_github · Team Ai