I hereby claim:
- I am erikgartner on github.
- I am erikgartner (https://keybase.io/erikgartner) on keybase.
- I have a public key ASAdw1HSlw2GJ1BWEZCBmt6wNjAhppKRRVL3ic_9Zj7Vqwo
To claim this, I am signing this object:
update_plex() { | |
tmp=$(mktemp)'.deb' | |
url=$1 | |
wget -O "$tmp" "$1" | |
sudo dpkg -i $tmp | |
rm -f $tmp | |
} |
for name in *.mp3; do | |
track=$(echo $name | cut -d - -f 1) | |
max_track=$(echo $name | cut -d - -f 2 | cut -d ' ' -f 1) | |
echo "$name - $track/$max_track" | |
id3v2 -T "$track/$max_track" "$name" | |
done |
I hereby claim:
To claim this, I am signing this object:
[Adblock Plus 2.0] | |
omni.se##article.article--sponsored |
import requests | |
import json | |
BASE_URL = 'http://whitewolf.wikia.com/' | |
def scrape_artifacts(offset=''): | |
path = 'api/v1/Articles/List' | |
query = { | |
'expand': 1, |
import csv | |
import requests | |
import sys | |
import json | |
LASTM_FM_KEY = '' | |
genre_cache = {} | |
#! /bin/sh | |
# Installs CUDA 8.0 (not cuDNN) on Ubuntu 16.04 (or equivalent). | |
# Remove old stuff | |
sudo apt remove --purge -y "*cuda*" "*nvidia*" "*cudnn*" | |
# Download CUDA | |
wget "https://developer.nvidia.com/compute/cuda/8.0/Prod2/local_installers/cuda-repo-ubuntu1604-8-0-local-ga2_8.0.61-1_amd64-deb" -O "cuda.deb" | |
wget "https://developer.nvidia.com/compute/cuda/8.0/Prod2/patches/2/cuda-repo-ubuntu1604-8-0-local-cublas-performance-update_8.0.61-1_amd64-deb" -O "cuda-patch.deb" |
### Keybase proof | |
I hereby claim: | |
* I am erikgartner on github. | |
* I am erikgartner (https://keybase.io/erikgartner) on keybase. | |
* I have a public key ASAx65x5aiAfExWxAwGGqaiMijfFIibSHDbALxpdqmTIDwo | |
To claim this, I am signing this object: |
This guide tries to make sense of installing NVIDIA CUDA on Ubuntu.
Disclaimer: Installing CUDA is a somewhat tedious and can be a problematic process. This guide worked for me, though if you have an unusual configuration you might need additional preparations to make this work. My machines are mostly blank Ubuntu machines.
For reference NVIDIA's official guides are here for CUDA and cuDNN.
Last updated: 2019-07-27