ROCm-AI-Installer

A script that automatically installs all the required stuff to run selected AI interfaces on AMD Radeon 7900XTX.

Info

Note

Ubuntu 24.04 is recommended. Version 4.0 is not tested on older versions.

Part of the installation script is based on this guide: https://github.com/nktice/AMD-AI/blob/main/ROCm6.0.md

Test platform:

Name	Info
CPU	AMD Ryzen 7900X3D (iGPU disabled in BIOS)
GPU	AMD Radeon 7900XTX
RAM	64GB DDR5 6600MHz
Motherboard	ASRock B650E PG Riptide WiFi (2.10)
OS	Ubuntu 24.04
Kernel	6.8.0-31-generic
ROCm	6.1.1

Text generation

Name	Enviroment	Links	Additional information
KoboldCPP	Python 3.11 venv	https://github.com/YellowRoseCx/koboldcpp-rocm
Text generation web UI	Python 3.11 venv	https://github.com/oobabooga/text-generation-webui https://github.com/arlo-phoenix/bitsandbytes-rocm-5.6 https://github.com/ROCmSoftwarePlatform/flash-attention https://github.com/turboderp/exllamav2	1. Tested: ExLlamav2, Transformers, llama.ccp 2. Requrements for Superbooga are installed, but the extension is not enabled by default
SillyTavern (1.12.0)	Node	https://github.com/SillyTavern/SillyTavern	1. Extras project is discontinued and removed from the script. https://github.com/SillyTavern/SillyTavern-Extras

Image generation

Name	Enviroment	Links	Additional information
Stable Diffusion web UI	Python 3.11 venv	https://github.com/AUTOMATIC1111/stable-diffusion-webui	1. Startup parameters are in the webui-user.sh file
ANIMAGINE XL 3.1	Python 3.12 venv	https://huggingface.co/spaces/cagliostrolab/animagine-xl-3.1 https://huggingface.co/cagliostrolab/animagine-xl-3.1

Music generation

Name	Enviroment	Links	Additional information
AudioCraft	Python 3.11 venv	https://github.com/facebookresearch/audiocraft

Voice generation

Name	Enviroment	Links	Additional information
WhisperSpeech web UI	Python 3.11 venv	https://github.com/Mateusz-Dera/whisperspeech-webui https://github.com/collabora/WhisperSpeech https://github.com/ROCmSoftwarePlatform/flash-attention

3D generation

Name	Enviroment	Links	Additional information
TripoSR	Python3.12 venv	https://github.com/VAST-AI-Research/TripoSR https://github.com/ROCmSoftwarePlatform/flash-attention.git	1. It uses PyTorch ROCm, but torchmcubes is built for the CPU. This method is still faster than using just PyTorch CPU-only version.

Instalation:

Note

First startup after installation of the selected interface may take longer.

Important

This script does not download any models. If the interface does not have defaults, download your own.

Caution

If you update, back up your settings and models. Reinstallation deletes the previous directories.

1. Add the user to the required groups.

sudo adduser `whoami` video
sudo adduser `whoami` render

2. Reboot

sudo reboot

3. Run installer

bash ./install.sh

4. Select installation path.
5. Select ROCm installation if you are upgrading or running the script for the first time.
6. Install selected interfaces
7. Go to the installation path with the selected interface and run:

./run.sh