... to my blog style space for easier contribution by third parties and to provide what I believe to be an easier reading experience. Please field all enquiries and issues to the source repository.
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
#!/usr/bin/env bash | |
set -e | |
cd ~ | |
sudo -v | |
# Make sure system is in a good, updated, clean, state. | |
sudo apt-get -y update |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
import torch | |
from diffusers import StableDiffusionPipeline | |
from torch import autocast | |
import random | |
import matplotlib.pyplot as plt | |
import os | |
prompts = [ | |
"1965 Porsche 911", |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
''' | |
Tutorial Code for distributed training in PyTorch that trains | |
an inception_v3 model on dummy data. | |
*Installation: * | |
Use pip/conda to install the following libraries | |
- torch | |
- torchvision | |
- argparse | |
- tqdm |
JSON containing links to the all known PaperMC versions.
Note
This JSON is being updated manually.
If you want to always have the most actual paper-versions.json
, check out this generator: qing762/paper-version-links (dynamic JSON)
Kudos to @qing762
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
# all imports | |
from IPython.display import Javascript | |
from google.colab import output | |
from base64 import b64decode | |
from io import BytesIO | |
!pip -q install pydub | |
from pydub import AudioSegment | |
RECORD = """ | |
const sleep = time => new Promise(resolve => setTimeout(resolve, time)) |