4.2 KiB
For Runpod/Vast instructions see Cloud Setup
For Google Colab see Train_Colab.ipynb
Install Python
Install Python 3.10 from here if you do not already have Python 3.10.x installed.
https://www.python.org/downloads/release/python-3109/
https://www.python.org/ftp/python/3.10.9/python-3.10.9-amd64.exe
Download and install Git from git-scm.com.
Make sure Python 3.10 shows on your command window:
python --version
You should see Python 3.10.something
. 3.10.5, 3.10.9, etc. It needs to be 3.10.x.
If you have Python 3.10.x installed but your command window shows another version (3.8.x, 3.9.x) ask for assistance in the discord. ...or you can try setting the path to the 310 binaries before running the windows_setup.cmd if you know what you're doing.
SET PYTHON=C:\Python310\python.exe
(you'll have to locate python 310 on your system on your own if you)
Clone this repo
Clone the repo from normal command line then change into the directory:
git clone https://github.com/victorchall/EveryDream2trainer
Then change into the folder:
cd EveryDream2trainer
Windows
While still in the command window, run windows_setup.cmd to create your venv and install dependencies.
windows_setup.cmd
Double check your python version again after setup by running these two commands:
activate_venv.bat
python --version
Again, this should show 3.10.x
Local docker container
docker compose up
And you can either get a shell via:
docker exec -it everydream2trainer-docker-everydream2trainer-1 /bin/bash
Or go to your browser and hit http://localhost:8888
. The web password is
test1234
but you can change that in docker-compose.yml
.
Your current source directory will be moutned to the Jupyter notebook.
Local Linux install
Preinstallation
- Make sure you have python3.10 installed. Often this is
python3
so check withpython3 -V
- Make sure Linux Nvidia driver is up to date and working.
Check that
nvidia-smi
is working and shows your GPU.
Steps to update the driver may depend on the Linux distribution you use. For Ubuntu, use Gnome and openSoftwrae & Updates
, go to theadditional drivers
tab and selectUsing NVIDIA driver metapackage from nvidia-driver-530 (proprietary)
. Currently530
is the latest version, but you can use latest at your time of install. You will need to use the proprietary driver. - Install Cuda 11.8. You can use this link for Ubuntu: https://developer.nvidia.com/cuda-11-8-0-download-archive?target_os=Linux&target_arch=x86_64&Distribution=Ubuntu&target_version=22.04&target_type=deb_local for Ubuntu 22.04 for instance. Your install may vary depending on Linux distribution, make sure to select appropriate options.
- Most problems arise from improper driver or cuda install and will not successfully run
nvidia-smi
(various errors likecommand not found
ordriver mismatch
). Make surenvidia-smi
runs and prints your GPU information before continuing. - Install git with
sudo apt-get git
- Suggested: Enable git lfs support, follow instructions: https://github.com/git-lfs/git-lfs/blob/main/INSTALLING.md
- Optional: Enable remote desktop and/or SSH (see instructions for your distribution)
- Optional if you'd rather use conda instead of VENV: Install miniconda,
wget
the appropriate bash script then run it: https://docs.conda.io/en/latest/miniconda.html#linux-installers
ED2 setup
git clone https://github.com/victorchall/EveryDream2trainer
cd EveryDream2trainer
python3 -m venv venv
source venv/bin/activate
At this point python -V
should return 3.10 and which python
should return something like /home/username/EveryDream2trainer/venv/bin/python
so you can just use python
to run instead of python3
if you like. YMMV based on distribution.
pip install -r requirements.txt
Should be good to go.
Conda should be something like this (untested)
git clone https://github.com/victorchall/EveryDream2trainer
cd EveryDream2trainer
conda create --name ed2 python=3.10
conda activate ed2
pip install -r requirements.txt