A medical textbook illustration in a scientific and educational digital illustration style, characterized by clean lines, clear rendering, and a bright, varied color palette with saturated but not overly vibrant hues. The lighting is consistent and even, with subtle gradients giving a sense of three-dimensionality. The overall impression is graphic and illustrative with a rendered, vector-like quality, smooth curves, and precise shapes, and a deliberate lack of texture, contributing to the clean and academic feel. The image depicts two identical black fur mice against a clear white background. Both mice were being sacrifice side to side. They were fixated on top of operating table for animals in a supine position exposing their abdomen along with surgical tools on the side. Both mice have rounded bodies, pointed snouts, and long, thin tails that curve slightly upwards at the end. Their ears are small and round.
ps aux | grep {process} # Track process using CPU
lsof -i :{port} # Identify app on network port
df -h # Check disk space (human-readable)
netstat -tulpn # Active network connections (or ss -tunlp)
kubectl get pods | grep -i error# Spot Kubernetes pod issues
top -o %CPU # Sort processes by CPU usage
For our bioinformatics analyses, we follow a standard procedure to ensure reproducibility, consistency, and clear tracking of results. The core components of this workflow standard are:
We package the specific version of each software tool and all its dependencies into a Docker image. This guarantees that the software environment is exactly the same every time we run an analysis, regardless of the system it's run on, avoiding 'it works on my machine' problems.
The entire analysis process for a given tool or step – from defining inputs and parameters to executing the core commands (like indexing, alignment, processing) – is written as a single shell script (.sh). This makes the analysis transparent, shareable, and easily repeatable. It's our 'recipe' for the analysis.
Every time a workflow script is executed, it automatically creates a new, unique directory stamped with the date and ti
--- | |
title: "<title>" | |
author: "<name>" | |
date: 'Compiled: `r format(Sys.Date(), "%B %d, %Y")`' | |
editor_options: | |
chunk_output_type: console | |
output: | |
html_document: | |
keep_md: true | |
engine: knitr |
🙋 I am developing a local LLM for personal and sensitive project. I want the LLM to have helpful character like you. What prompt should I put into it?
🤖 To create a local LLM with a helpful character like mine, you’ll want to craft a system prompt that defines its tone, behavior, and approach to tasks while ensuring it respects privacy and sensitivity for your personal project. Below is a suggested system prompt, followed by some guidance on tailoring it to your needs.
You are a highly helpful, friendly, and trustworthy AI assistant designed to assist with personal and sensitive projects. Your goal is to provide accurate, concise, and thoughtful responses tailored to the user's needs. Follow these guidelines:
colima status
If not running, start it. Allocate sufficient resources.
- runtime docker: specifies using Docker (vs. containerd)
- cpu 6: Allocate 4 CPU cores to the VM. <redacted>iMac has 8
- memory 8: Allocate 8 GB RAM to the VM. <redacted>iMac has 16
- disk 50: Allocate 50 GB disk space to the VM. <redacted>iMac has 8
Note: I have moved this list to a proper repository. I'll leave this gist up, but it won't be updated. To submit an idea, open a PR on the repo.
Note that I have not tried all of these personally, and cannot and do not vouch for all of the tools listed here. In most cases, the descriptions here are copied directly from their code repos. Some may have been abandoned. Investigate before installing/using.
The ones I use regularly include: bat, dust, fd, fend, hyperfine, miniserve, ripgrep, just, cargo-audit and cargo-wipe.
Thanks everyone for commenting/contributing! I made this in college for a class and I no longer really use the technology. I encourage you all to help each other, but I probably won't be answering questions anymore.
This article is also on my blog: https://emilykauffman.com/blog/install-anaconda-on-wsl
Note: $
denotes the start of a command. Don't actually type this.
- Install WSL (Ubuntu for Windows - can be found in Windows Store). I recommend the latest version (I'm using 18.04) because there are some bugs they worked out during 14/16 (microsoft/WSL#785)
- Go to https://repo.continuum.io/archive to find the list of Anaconda releases
- Select the release you want. I have a 64-bit computer, so I chose the latest release ending in
x86_64.sh
. If I had a 32-bit computer, I'd select thex86.sh
version. If you accidentally try to install the wrong one, you'll get a warning in the terminal. I chose `Anaconda3-5.2.0-Li
// Place your key bindings in this file to override the defaults | |
[ | |
// keybindings for R scripts, Rmarkdown, Quarto, and R terminal (radian included) | |
{ | |
"key": "Ctrl+Shift+m", | |
"command": "type", | |
"args": { | |
"text": " %>% " | |
}, | |
"when": "editorTextFocus && (editorLangId == r || editorLangId == rmd || editorLangId == quarto)" |