-
At the root of the repository, create a
.prettierrcfile:{ "plugins": ["prettier-plugin-go-template"], "overrides": [ { "files": ["*.html"],
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| # AUTOMATE UDIO | |
| # by DADABOTS dadabots.com | |
| # was working on 2024-04-13 | |
| # tldr; get your login cookie, use it to automate udio from python | |
| import requests | |
| import json | |
| from time import sleep | |
| import re |
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| // ==UserScript== | |
| // @name ChatGPT CSS fixes | |
| // @version 2025-12-19.2 | |
| // @description Adjusts the ChatGPT web UI for convenience: wider chat area, colored message bubbles, clearer code blocks, multi-line history items, and a few other tweaks for heavy ChatGPT use. ❤️ If you like this, consider buying me a coffee: ko-fi.com/alexchexes ❤️ | |
| // @updateURL https://gist.github.com/alexchexes/d2ff0b9137aa3ac9de8b0448138125ce/raw/chatgpt_ui_fix.user.js | |
| // @downloadURL https://gist.github.com/alexchexes/d2ff0b9137aa3ac9de8b0448138125ce/raw/chatgpt_ui_fix.user.js | |
| // @author alexchexes | |
| // @website https://ko-fi.com/alexchexes | |
| // @namespace http://tampermonkey.net/ | |
| // @match https://chat.openai.com/* |
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| import os | |
| import torch | |
| import time | |
| from diffusers import DiffusionPipeline, AutoencoderTiny | |
| from collections import namedtuple | |
| PredictionResult = namedtuple('PredictionResult', [ | |
| 'latents', | |
| 'step', | |
| 'steps', |
Latest Update: May 19th, 2024
This gist contains all the steps required to:
- Install multiple CUDA versions (e.g.,
CUDA 11.8 andCUDA 12.1 - Manage multiple CUDA environments on Ubuntu using the utility called environment modules.
- Use this approach to avoid CUDA environment conflicts.
Environment Modules is a package that provides for the dynamic modification of a user's environment via modulefiles. You can find more on it at https://modules.readthedocs.io/en/latest/
It contains steps for installing CUDA. It further shows how one can install Tensorflow and Pytorch and use GPUs with them.Our motive is to get output as in the image below,
where nvidia-smi, nvcc --version, torch.cuda.is_available(),tf.test.gpu_devic_name() all are working. Let's go then. I will specifically install CUDA 10.1 where both Tensorflow and Pytorch works fine.
https://gist.github.com/victor-shepardson/5b3d3087dc2b4817b9bffdb8e87a57c4
I'm using Ubuntu 16.04 with a GTX 1060
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