Installation script for an AI applications using ROCm on Linux.
50
stars
591
commits
Shell
primary language
Sep 5, 2026
updated
Installation scripts for an AI applications using ROCm on Linux.
[!Important] All models and applications are tested on a GPU with 24GB of VRAM.
Some applications may not work on GPUs with less VRAM.
| Name | Info |
|---|---|
| CPU | AMD Ryzen 9 9950X3D |
| GPU | AMD Radeon 7900XTX |
| RAM | 64GB DDR5 6600MHz |
| Motherboard | Gigabyte X870 AORUS ELITE WIFI7 (BIOS F8) |
| OS | Debian 13.6 |
| Kernel | 6.12.107+deb13-amd64 |
| Name | Links | API | GUI | Additional information |
|---|---|---|---|---|
| SillyTavern | SillyTavern/SillyTavern | - | 8000 | 1. Basic auth enabled, defaults: user / password. 2. Change in config.yaml. |
| llama.cpp TurboQuant | TheTom/llama-cpp-turboquant unsloth/gemma-4-26B-A4B-it-qat-GGUF | 8080 | 8080 | 1. Available as ROCm or Vulkan build. 2. TurboQuant 3-bit KV cache. 3. Model: gemma-4-26B-A4B-it-qat Q4_K_XL with its MTP 4. GGUF: user-models/ 5. MTP: drafts/. 6. Models: models.ini |
| KoboldCPP | YellowRoseCx/koboldcpp-rocm | 5001 | 5001 | |
| vLLM Gemma 4 | vllm-project/vllm 0xSero/turboquant google/gemma-4-31B-it-qat | 8002 | - | 1. TurboQuant 4-bit KV cache. 2. Model: gemma-4-31B-it-qat, quantized to W4A16 during install. 3. ~59GB download, ~50GB RAM for the conversion. |
| Name | Links | API | GUI | Additional information |
|---|---|---|---|---|
| ComfyUI | Comfy-Org/ComfyUI city96/ComfyUI-GGUF | 8188 | 8188 | Workflows templates are in the workflows folder. Extension manager is installed by default. ComfyUI-GGUF is installed by default. |
| Krea 2 Turbo + Edit | krea-ai/krea-2 krea/Krea-2-Turbo krea/krea-2-loras conradlocke/krea2-identity-edit lbouaraba/comfyui-krea2edit | - | 7860 | 1. Custom UI. 2. 4-bit NF4 quantization. 3. Turbo model (8 steps). 4. 9 official style LoRAs. 5. Custom LoRA supported. 6. Identity Edit LoRA 7. Krea 2 and the LoRAs are licensed under the Krea 2 Community License Agreement: the weights are gated, so accept it on the model page and set HuggingFace Token in Variables. 8. Commercial use only below 1,000,000USD annual revenue; outputs are AI-generated and must be disclosed as such where required. |
| Name | Link |
|---|---|
| Z-Image-Turbo | Tongyi-MAI/Z-Image-Turbo Comfy-Org/z_image_turbo |
| Z-Anime | SeeSee21/Z-Anime Comfy-Org/z_image_turbo |
| Wan2.2-TI2V-5B | Wan-AI/Wan2.2-TI2V-5B Comfy-Org/Wan_2.2_ComfyUI_Repackaged |
| Name | Links | GUI | Additional information |
|---|---|---|---|
| ACE-Step-1.5 | ace-step/ACE-Step-1.5 | 7860 |
| Name | Links | GUI | Additional information |
|---|---|---|---|
| Soprano | ekwek1/soprano Mateusz-Dera/soprano-rocm | 7860 | |
| OmniVoice | k2-fsa/OmniVoice | 7860 | |
| Parakeet | nvidia/parakeet-tdt-0.6b-v3 | 7860 | 1. Added custom simple UI. |
| Name | Links | API | GUI | Additional information |
|---|---|---|---|---|
| PartCrafter | wgsxm/PartCrafter Mateusz-Dera/pytorch_cluster_rocm | - | 7860 | 1. Added custom simple UI. |
| trellis.cpp | pwilkin/trellis.cpp ilintar/trellis2-gguf | 8081 | 7860 | 1. Added custom simple UI. 2. Available as ROCm or Vulkan build. |
| ARDY | nv-tlabs/ardy meta-llama/Meta-Llama-3-8B-Instruct | - | 2333 | |
| TripoSplat | VAST-AI-Research/TripoSplat | - | 7860 | |
| AutoRemesher | huxingyi/autoremesher | - | - | 1. Automatic quad-remeshing tool. |
1. Install Podman.
[!Note] If you are using Debian 13.6, you can use sudo apt-get update && sudo apt-get -y install podman podman-compose qemu-system (should also work on Ubuntu 26.04)
[!Note] The installer menus need whiptail. It is preinstalled on most systems; if it is missing the script says so and exits.
2. Make sure that /dev/dri and /dev/kfd are accessible.
ls /dev/dri
ls /dev/kfd
[!Important] Your distribution must have amdgpu configured.
3. Make sure that your user has permissions for the video and render groups.
sudo usermod -aG video,render $USER
[!Important] If not, you need reboot after this step.
4. Clone repository.
git clone https://github.com/Mateusz-Dera/ROCm-AI-Installer.git
5. Run installer.
./install.sh
6. Set variables
[!Important] From version 17, ROCm packages are installed per GPU architecture. The installer reads the cards from the kernel and preselects them under GFX, and the container is built with the packages for those architectures only - not for every GPU AMD ships.
Selecting more than one architecture is supported, so a machine with, say, a gfx1100 card and a gfx1036 integrated GPU can have both. Changing the selection requires recreating the container.
[!Note] Using several cards at once has not been tested. The installer can build for more than one architecture, and each application is pinned to a single card when it is installed, but everything here was only ever run on a single GPU.
7. Create a container if you are upgrading or running the script for the first time.
8. Install the applications of your choice.
[!NOTE] With more than one usable card, each application asks which one it should run on while it is being installed. The answer is written into that application's run.sh as HIP_VISIBLE_DEVICES, so different applications can use different cards - image generation on the discrete GPU, something small on the integrated one.
There is no container-wide setting for this.
To change it later, edit HIP_VISIBLE_DEVICES in the application's run.sh or reinstall the application.
9. Go to the application folder and run:
./run.sh
[!NOTE] Everything is configured to start from the host side (You don't need to enter the container).
To check if the container is running:
podman ps
If the container is not running, start it with:
podman start rocm
To enter the container's bash shell:
podman exec -it rocm bash
To stop and remove the container:
podman stop rocm
podman rm rocm
Or force remove (stop and remove in one command):
podman rm -f rocm
590 commits
1 commits
Shell
51.3%
Python
47.7%
Dockerfile
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Installation script for an AI applications using ROCm on Linux.
50
stars
591
commits
Shell
primary language
Sep 5, 2026
updated
Installation scripts for an AI applications using ROCm on Linux.
[!Important] All models and applications are tested on a GPU with 24GB of VRAM.
Some applications may not work on GPUs with less VRAM.
| Name | Info |
|---|---|
| CPU | AMD Ryzen 9 9950X3D |
| GPU | AMD Radeon 7900XTX |
| RAM | 64GB DDR5 6600MHz |
| Motherboard | Gigabyte X870 AORUS ELITE WIFI7 (BIOS F8) |
| OS | Debian 13.6 |
| Kernel | 6.12.107+deb13-amd64 |
| Name | Links | API | GUI | Additional information |
|---|---|---|---|---|
| SillyTavern | SillyTavern/SillyTavern | - | 8000 | 1. Basic auth enabled, defaults: user / password. 2. Change in config.yaml. |
| llama.cpp TurboQuant | TheTom/llama-cpp-turboquant unsloth/gemma-4-26B-A4B-it-qat-GGUF | 8080 | 8080 | 1. Available as ROCm or Vulkan build. 2. TurboQuant 3-bit KV cache. 3. Model: gemma-4-26B-A4B-it-qat Q4_K_XL with its MTP 4. GGUF: user-models/ 5. MTP: drafts/. 6. Models: models.ini |
| KoboldCPP | YellowRoseCx/koboldcpp-rocm | 5001 | 5001 | |
| vLLM Gemma 4 | vllm-project/vllm 0xSero/turboquant google/gemma-4-31B-it-qat | 8002 | - | 1. TurboQuant 4-bit KV cache. 2. Model: gemma-4-31B-it-qat, quantized to W4A16 during install. 3. ~59GB download, ~50GB RAM for the conversion. |
| Name | Links | API | GUI | Additional information |
|---|---|---|---|---|
| ComfyUI | Comfy-Org/ComfyUI city96/ComfyUI-GGUF | 8188 | 8188 | Workflows templates are in the workflows folder. Extension manager is installed by default. ComfyUI-GGUF is installed by default. |
| Krea 2 Turbo + Edit | krea-ai/krea-2 krea/Krea-2-Turbo krea/krea-2-loras conradlocke/krea2-identity-edit lbouaraba/comfyui-krea2edit | - | 7860 | 1. Custom UI. 2. 4-bit NF4 quantization. 3. Turbo model (8 steps). 4. 9 official style LoRAs. 5. Custom LoRA supported. 6. Identity Edit LoRA 7. Krea 2 and the LoRAs are licensed under the Krea 2 Community License Agreement: the weights are gated, so accept it on the model page and set HuggingFace Token in Variables. 8. Commercial use only below 1,000,000USD annual revenue; outputs are AI-generated and must be disclosed as such where required. |
| Name | Link |
|---|---|
| Z-Image-Turbo | Tongyi-MAI/Z-Image-Turbo Comfy-Org/z_image_turbo |
| Z-Anime | SeeSee21/Z-Anime Comfy-Org/z_image_turbo |
| Wan2.2-TI2V-5B | Wan-AI/Wan2.2-TI2V-5B Comfy-Org/Wan_2.2_ComfyUI_Repackaged |
| Name | Links | GUI | Additional information |
|---|---|---|---|
| ACE-Step-1.5 | ace-step/ACE-Step-1.5 | 7860 |
| Name | Links | GUI | Additional information |
|---|---|---|---|
| Soprano | ekwek1/soprano Mateusz-Dera/soprano-rocm | 7860 | |
| OmniVoice | k2-fsa/OmniVoice | 7860 | |
| Parakeet | nvidia/parakeet-tdt-0.6b-v3 | 7860 | 1. Added custom simple UI. |
| Name | Links | API | GUI | Additional information |
|---|---|---|---|---|
| PartCrafter | wgsxm/PartCrafter Mateusz-Dera/pytorch_cluster_rocm | - | 7860 | 1. Added custom simple UI. |
| trellis.cpp | pwilkin/trellis.cpp ilintar/trellis2-gguf | 8081 | 7860 | 1. Added custom simple UI. 2. Available as ROCm or Vulkan build. |
| ARDY | nv-tlabs/ardy meta-llama/Meta-Llama-3-8B-Instruct | - | 2333 | |
| TripoSplat | VAST-AI-Research/TripoSplat | - | 7860 | |
| AutoRemesher | huxingyi/autoremesher | - | - | 1. Automatic quad-remeshing tool. |
1. Install Podman.
[!Note] If you are using Debian 13.6, you can use sudo apt-get update && sudo apt-get -y install podman podman-compose qemu-system (should also work on Ubuntu 26.04)
[!Note] The installer menus need whiptail. It is preinstalled on most systems; if it is missing the script says so and exits.
2. Make sure that /dev/dri and /dev/kfd are accessible.
ls /dev/dri
ls /dev/kfd
[!Important] Your distribution must have amdgpu configured.
3. Make sure that your user has permissions for the video and render groups.
sudo usermod -aG video,render $USER
[!Important] If not, you need reboot after this step.
4. Clone repository.
git clone https://github.com/Mateusz-Dera/ROCm-AI-Installer.git
5. Run installer.
./install.sh
6. Set variables
[!Important] From version 17, ROCm packages are installed per GPU architecture. The installer reads the cards from the kernel and preselects them under GFX, and the container is built with the packages for those architectures only - not for every GPU AMD ships.
Selecting more than one architecture is supported, so a machine with, say, a gfx1100 card and a gfx1036 integrated GPU can have both. Changing the selection requires recreating the container.
[!Note] Using several cards at once has not been tested. The installer can build for more than one architecture, and each application is pinned to a single card when it is installed, but everything here was only ever run on a single GPU.
7. Create a container if you are upgrading or running the script for the first time.
8. Install the applications of your choice.
[!NOTE] With more than one usable card, each application asks which one it should run on while it is being installed. The answer is written into that application's run.sh as HIP_VISIBLE_DEVICES, so different applications can use different cards - image generation on the discrete GPU, something small on the integrated one.
There is no container-wide setting for this.
To change it later, edit HIP_VISIBLE_DEVICES in the application's run.sh or reinstall the application.
9. Go to the application folder and run:
./run.sh
[!NOTE] Everything is configured to start from the host side (You don't need to enter the container).
To check if the container is running:
podman ps
If the container is not running, start it with:
podman start rocm
To enter the container's bash shell:
podman exec -it rocm bash
To stop and remove the container:
podman stop rocm
podman rm rocm
Or force remove (stop and remove in one command):
podman rm -f rocm
590 commits
1 commits
Shell
51.3%
Python
47.7%
Dockerfile
1.0%