pepeai-testnet

experimental testnet for decentralized p2p AI processing

Setting up the environment:

Nvidia Driver:

sudo apt-get update && sudo apt-get install nvidia-driver-530

Docker:

Linux
Windows
OSX

sudo docker run -p 31330:31330 --ipc host --gpus all --volume petals-cache:/cache --rm     learningathome/petals:main python -m petals.cli.run_server bigscience/bloomz-petals --initial_peers /ip4/54.164.52.79/tcp/8989/p2p/QmR7G6GZzeQeJoXfTovp8PJdJ7qxKYFwXUa2fp9p6BYdDi --port 31330

Or install manually:

Anaconda Install:

wget https://repo.anaconda.com/archive/Anaconda3-2023.03-1-Linux-x86_64.sh
chmod +x ./Anaconda3-2023.03-1-Linux-x86_64.sh
./Anaconda3-2023.03-1-Linux-x86_64.sh

Answer yes to base env setup.

conda create -n pepeaitestnet python=3.10
conda activate pepeaitestnet
conda install pytorch pytorch-cuda=11.7 -c pytorch -c nvidia
pip install -U petals

Running a Node:

PepeAI net seperates processing by PepeCoin Nodes. Each node requires at least 1 GPU w/ 8GB+ or more of memory.

bloom model layers distrubuted across fleet of pepecoin nodes
will support various models as they are updated for pepecoin ai net

Start GPU Processing Node:

ensure environment is setup as indicated above
If you have more than 1 GPU, set the GPU index before starting the node
you can run multiple nodes under screen
optional IP:PORT for improved network performance, use --public_ip x.x.x.x --port 8989
from linux cli, to get public ip

curl ifconfig.me

Run Node (don't forget to add --port 8989 --public_ip x.x.x.x) if you have setup port forwarding on your router

export CUDA_VISIBLE_DEVICES=0  # Insert the GPU index here, counting from zero
python -m petals.cli.run_server bigscience/bloomz-petals --initial_peers /ip4/54.164.52.79/tcp/8989/p2p/QmR7G6GZzeQeJoXfTovp8PJdJ7qxKYFwXUa2fp9p6BYdDi

Demo Chatbot:

python3 ./pepeaichatbot.py

PepeAIDex's Projects

computer-science

:mortar_board: Path to a free self-taught education in Computer Science!

This is literally a game framework, based on Unity game engine. It encapsulates commonly used game modules during development, and, to a large degree, standardises the process, enhances the development speed and ensures the product quality.