komikndr

What it is

This is my OpenCode setup for local models, mainly using a customized llama.cpp configuration.

For Qwen 3.8, DeepSeek V4, and Glimmer, the models are already trained to support reasoning effort levels. Depending on the model, these may be exposed as low, medium, high, xhigh, or as low, high, and max.

For models that support reasoning but were not trained with explicit reasoning-effort levels, such as the Qwen 3.5 and 3.6 variants, I use a token budget to limit the amount of reasoning.

Although Qwen 3.8 has built-in reasoning-effort levels, I still apply a maximum reasoning-token cap for each effort level.

Although the llama.cpp CLI flags specify preserve_thinking and a default reasoning budget, these can still be overridden through the API, so this works fine for my setup.

tkafka

Electron Apps Causing System-Wide Lag on Tahoe

This script detects apps with not yet updated versions of Electron.

Repo: https://github.com/tkafka/detect-electron-apps-on-mac

See:

• electron/electron#48311 (comment)
• Michael Tsai: Electron Apps Causing System-Wide Lag on Tahoe

aaronwolen

README

Setup

Use conda to install the TileDB Python API and other dependencies.

mamba env create -f environment.yaml
conda activate aind-demo

benmarwick

# Adapted from https://stackoverflow.com/a/7267364/1036500 by Andrie de Vries

# This is it: theme(axis.text.x = element_text(angle = 90, hjust = 1, vjust = 0.5))

library(ggplot2)

td <- expand.grid(
  hjust=c(0, 0.5, 1),
  vjust=c(0, 0.5, 1),
  angle=c(0, 45, 90),

mbinna

Effective Modern CMake

Getting Started

For a brief user-level introduction to CMake, watch C++ Weekly, Episode 78, Intro to CMake by Jason Turner. LLVM’s CMake Primer provides a good high-level introduction to the CMake syntax. Go read it now.

After that, watch Mathieu Ropert’s CppCon 2017 talk Using Modern CMake Patterns to Enforce a Good Modular Design (slides). It provides a thorough explanation of what modern CMake is and why it is so much better than “old school” CMake. The modular design ideas in this talk are based on the book [Large-Scale C++ Software Design](https://www.amazon.de/Large-Scale-Soft

HenrikBengtsson

WORK FLOW: Git and Bioconductor SVN (2016)

This is how I currently work with Git and the Bioconductor SVN. I'll use the affxparser package as an example.

Clone existing Git repository

% git clone git@github.com:HenrikBengtsson/affxparser.git
% cd affxparser

Checkout existing Git Flow branches

I'm using the Git Flow workflow everywhere, including this package. In short,

imjasonh

* {
    font-size: 12pt;
    font-family: monospace;
    font-weight: normal;
    font-style: normal;
    text-decoration: none;
    color: black;
    cursor: default;
}

D-side

// Jekyll Pygments syntax highlighter styles

// Color scheme
$base03:                   #002B36
$base02:                   #073642
$base01:                   #586E75
$base00:                   #657B83
$base0:                    #839496
$base1:                    #93A1A1
$base2:                    #EEE8D5

kates

ag "sometext" --nogroup | awk '{print substr($1,1,index($1,":")-1);}' | xargs -I {} sed -i .bak -e 's/sometext/anothertext/g' {}

chrislkeller

/**
 * Retrieves all the rows in the active spreadsheet that contain data and logs the
 * values for each row.
 * For more information on using the Spreadsheet API, see
 * https://developers.google.com/apps-script/service_spreadsheet
 */
function readRows() {
  var sheet = SpreadsheetApp.getActiveSheet();
  var rows = sheet.getDataRange();
  var numRows = rows.getNumRows();