Note: I haven't documented CUDA here. I'm lazy (and haven't tested on Arch). See https://documentation.ubuntu.com/wsl/en/latest/howto/gpu-cuda for that on Ubuntu.
So I got this working on both Ubuntu, and Arch. First, start with a fresh install (of archlinux from https://gitlab.archlinux.org/archlinux/archlinux-wsl or Ubuntu from
wsl --install Ubuntuor https://apps.microsoft.com/detail/9pdxgncfsczv).
Download and install these two CLI tools:
Create a permanent folder on your file explorer named something like BetterDiscordReinstall.
Depending on your Discord client, place the two batch programs in the folder:
| Name | Input | Output | |
|---|---|---|---|
| Gemini 2.0 Flash-Lite | $0.075 | $0.30 | |
| Mistral 3.1 Small | $0.10 | $0.30 | |
| Gemini 2.0 Flash | $0.10 | $0.40 | |
| ChatGPT 4.1-nano | $0.10 | $0.40 | |
| DeepSeek v3 (old) | $0.14 | $0.28 | |
| ChatGPT 4o-mini | $0.15 | $0.60 | |
| Gemini 2.5 Flash | $0.15 | $0.60 | |
| DeepSeek v3 | $0.27 | $1.10 | |
| Grok 3-mini | $0.30 | $0.50 |
For some reason, Twilio has disabled the ability to install the iPad version of Authy on Apple Silicon Macs. With Authy Desktop also being discontinued, this means that there is no longer an official way to use the Authy app on macOS anymore. This guide is a workaround I found to trick sideloaded versions of Authy into signing in successfully, and using that with a sideloaded version of the Authy iPad app on macOS gives us the ability to use Authy on Mac again.
What's needed for this guide:
This is a fake exploit scam on gift card sites.
The scam seems to be atleast distributed here:
The usescript is under handle "Hadez", one of the google drive documents is made on Google account:
[email protected]hihuchanafare
| // ==UserScript== | |
| // @name Medium Paywall Bypass | |
| // @namespace Violentmonkey Scripts | |
| // @run-at document-start | |
| // @match *://*/* | |
| // @grant none | |
| // @version 2.4_4 | |
| // @updateURL https://gist.githubusercontent.com/zzJinux/364725e7c61810719286d94e88a4e38c/raw/medium.user.js | |
| // @downloadURL https://gist.githubusercontent.com/zzJinux/364725e7c61810719286d94e88a4e38c/raw/medium.user.js | |
| // @website https://freedium.cfd |
| git clone https://github.com/OpenDevin/OpenDevin.git | |
| cd OpenDevin | |
| conda create -n od python=3.10 | |
| conda activate od | |
| docker ps | |
| (optional) install docker if not already installed | |
| docker pull ghcr.io/opendevin/sandbox | |
| export OPENAI_API_KEY={your key} | |
| (optional I had to install rust) curl --proto '=https' --tlsv1.2 -sSf [https://sh.rustup.rs](https://sh.rustup.rs/) | sh | |
| (optional) restart terminal |
Good question! I am collecting human data on how quantization affects outputs. See here for more information: ggml-org/llama.cpp#5962
In the meantime, use the largest that fully fits in your GPU. If you can comfortably fit Q4_K_S, try using a model with more parameters.
See the wiki upstream: https://github.com/ggerganov/llama.cpp/wiki/Feature-matrix
| // ==UserScript== | |
| // @name Medium Paywall Bypass | |
| // @namespace Violentmonkey Scripts | |
| // @run-at document-start | |
| // @match *://*.medium.com/* | |
| // @match *://medium.com/* | |
| // @match *://*/* | |
| // @grant none | |
| // @version 2.4 | |
| // @inject-into content |
Docker compose has nice support for GPUs, K8s has moved their cluster-wide GPU scheduler from experimental to stable status. Docker swarm has yet to support the device option used in docker compose so the mechanisms for supporting GPUs on swarm are a bit more open-ended.
Default Runtime: nvidia for swarm mode.