?一、軟件介紹
文末提供程序和源碼下載
? ? ? ? 一個開源腳本，可自動安裝在 AMD Radeon 7900XTX 上運行選定 AI 接口所需的所有內容。
二、ROCm-AI-Installer?ROCm-AI-安裝程序
一個開源腳本，可自動安裝在 AMD Radeon 7900XTX 上運行選定 AI 接口所需的所有內容。它也應該適用于 7900XT 卡。對于其他卡，請在腳本開頭更改 HSA_OVERRIDE_GFX_VERSION 和 GFX（未測試）
Note?注意
Ubuntu 24.04.2 LTS is recommended. Version 7.x is not tested on older systems.
建議使用 Ubuntu 24.04.2 LTS。版本 7.x 未在較舊的系統上進行測試。
Test platform:?測試平臺：
| Name?名字 | Info?信息 |
|---|---|
| CPU?中央處理器 | AMD Ryzen 9950X3D (iGPU disabled in BIOS) AMD Ryzen 9950X3D（iGPU 在 BIOS 中禁用） |
| GPU?圖形處理器 | AMD Radeon 7900XTX?AMD Radeon 7900XTX 顯卡 |
| RAM?公羊 | 64GB DDR5 6600MHz |
| Motherboard?母板 | ASRock B650E PG Riptide WiFi (BIOS 3.20) 華擎 B650E PG Riptide WiFi （BIOS 3.20） |
| OS | Ubuntu 24.04.2 LTS |
| Kernel?內核 | 6.11.0-25-generic?6.11.0-25-通用 |
| ROCm | 6.4 |
Text generation?文本生成
| Name?名字 | Links?鏈接 | Additional information?其他信息： |
|---|---|---|
| KoboldCPP?狗頭人CPP | GitHub - YellowRoseCx/koboldcpp-rocm: AI Inferencing at the Edge. A simple one-file way to run various GGML models with KoboldAI's UI with AMD ROCm offloading | 1. Support GGML and GGUF models. 1. 支持 GGML 和 GGUF 模型。 |
| Text generation web UI 文本生成 Web UI | GitHub - oobabooga/text-generation-webui: A Gradio web UI for Large Language Models with support for multiple inference backends. GitHub - ROCm/bitsandbytes: 8-bit CUDA functions for PyTorch GitHub - turboderp-org/exllamav2: A fast inference library for running LLMs locally on modern consumer-class GPUs | 1. Support ExLlamaV2, Transformers using ROCm and llama.cpp using Vulkan. 1. 支持 ExLlamaV2、使用 ROCm 的 Transformers 和使用 Vulkan 的 llama.cpp。 |
| SillyTavern?SillyTavern （愚蠢酒館） | GitHub - SillyTavern/SillyTavern: LLM Frontend for Power Users. | |
| llama.cpp | GitHub - ggml-org/llama.cpp: LLM inference in C/C++ | 1. Put model.gguf into llama.cpp folder. 1. 將 model.gguf 放入 llama.cpp 文件夾中。 2. Change context size in run.sh file (Default: 32768). 2. 更改文件中 run.sh 上下文大小（默認值：32768）。 3. Set GPU offload layers in run.sh file (Default: 1) 3. 在 run.sh 文件中設置 GPU 卸載圖層（默認值：1） |
Image generation?圖像生成
| Name?名字 | Links?鏈接 | Additional information?其他信息： |
|---|---|---|
| ComfyUI?舒適用戶界面 | GitHub - comfyanonymous/ComfyUI: The most powerful and modular diffusion model GUI, api and backend with a graph/nodes interface. | 1. Workflows templates are in the workflows folder. 1. 工作流模板位于 workflows 文件夾中。 |
| Artist?藝術家 | GitHub - songrise/Artist: Official repo for DiffArtist: Towards Structure and Appearance Controllable Image Stylization |
ComfyUI Addons?ComfyUI 插件
Important?重要
For GGUF models:?對于 GGUF 型號：
1. Accept accept the conditions to access its files and content on HugginFace website:
1. 接受接受 HugginFace 網站訪問其文件和內容的條件：
https://huggingface.co/black-forest-labs/FLUX.1-schnell
2. HugginFace token is required during installation.
2. 安裝時需要 HugginFace 令牌。
| Name?名字 | Link?鏈接 | Additional information?其他信息： |
|---|---|---|
| ComfyUI-Manager?ComfyUI-管理器 | GitHub - Comfy-Org/ComfyUI-Manager: ComfyUI-Manager is an extension designed to enhance the usability of ComfyUI. It offers management functions to install, remove, disable, and enable various custom nodes of ComfyUI. Furthermore, this extension provides a hub feature and convenience functions to access a wide range of information within ComfyUI. | Manage nodes of ComfyUI. 管理 ComfyUI 的節點。 |
| ComfyUI-GGUF?舒適UI-GGUF | GitHub - city96/ComfyUI-GGUF: GGUF Quantization support for native ComfyUI models https://huggingface.co/city96/t5-v1_1-xxl-encoder-bf16 https://huggingface.co/openai/clip-vit-large-patch14 https://huggingface.co/black-forest-labs/FLUX.1-schnell | GGUF models loader.?GGUF 模型加載器。 |
| ComfyUI-AuraSR?舒適UI-AuraSR | GitHub - alexisrolland/ComfyUI-AuraSR: Custom nodes for ComfyUI to run AuraSR models. https://huggingface.co/fal/AuraSR https://huggingface.co/fal/AuraSR-v2 | ComfyUI node to upscale images. ComfyUI 節點來放大圖像。 |
| AuraFlow-v0.3?光流 v0.3 | https://huggingface.co/fal/AuraFlow-v0.3 | Text to image model. 文本到圖像模型。 |
| FLUX.1-schnell GGUF | https://huggingface.co/black-forest-labs/FLUX.1-schnell https://huggingface.co/city96/FLUX.1-schnell-gguf | Text to image model. 文本到圖像模型。 |
| AnimePro FLUX GGUF | https://huggingface.co/advokat/AnimePro-FLUX | Text to image model. 文本到圖像模型。 |
| Flex.1-alpha GGUF | https://huggingface.co/ostris/Flex.1-alpha https://huggingface.co/hum-ma/Flex.1-alpha-GGUF | Text to image model. 文本到圖像模型。 |
Video generation?視頻生成
| Name?名字 | Links?鏈接 | Additional information?其他信息： |
|---|---|---|
| Cinemo?西莫 | https://huggingface.co/spaces/maxin-cn/Cinemo GitHub - maxin-cn/Cinemo: [CVPR 2025] Consistent and Controllable Image Animation with Motion Diffusion Models | 1. Interface PyTorch uses PyTorch 2.4.0 1. 接口 PyTorch 使用 PyTorch 2.4.0 |
Music generation?音樂生成
| Name?名字 | Links?鏈接 | Additional information?其他信息： |
|---|---|---|
| ACE-Step?ACE 步 | GitHub - ace-step/ACE-Step: ACE-Step: A Step Towards Music Generation Foundation Model |
Voice generation?語音生成
| Name?名字 | Links?鏈接 | Additional information?其他信息： |
|---|---|---|
| WhisperSpeech web UI?WhisperSpeech 網頁 UI | GitHub - Mateusz-Dera/whisperspeech-webui: Simple WhisperSpeech web UI GitHub - WhisperSpeech/WhisperSpeech: An Open Source text-to-speech system built by inverting Whisper. | |
| F5-TTS?F5-TTS 系列 | GitHub - SWivid/F5-TTS: Official code for "F5-TTS: A Fairytaler that Fakes Fluent and Faithful Speech with Flow Matching" | 1. Remember to select the voice file when using the interface. 1. 使用界面時記得選擇語音文件。 |
| Matcha-TTS?抹茶-TTS | GitHub - shivammehta25/Matcha-TTS: [ICASSP 2024] 🍵 Matcha-TTS: A fast TTS architecture with conditional flow matching | |
| Dia?日 | GitHub - nari-labs/dia: A TTS model capable of generating ultra-realistic dialogue in one pass. GitHub - tralamazza/dia: A TTS model capable of generating ultra-realistic dialogue in one pass. | 1. Script uses the optional-rocm-cuda fork by tralamazza. 1. 腳本使用 tralamazza 的 optional-rocm-cuda fork。 |
| Orpheus-TTS | https://huggingface.co/spaces/MohamedRashad/Orpheus-TTS/tree/main GitHub - canopyai/Orpheus-TTS: Towards Human-Sounding Speech | 1. If GPU is not detected change HIP_VISIBLE_DEVICES value. 1. 如果未檢測到 GPU，請更改 HIP_VISIBLE_DEVICES 值。 |
| IMS-Toucan?IMS-巨嘴鳥 | GitHub - DigitalPhonetics/IMS-Toucan: Controllable and fast Text-to-Speech for over 7000 languages! | 1. PyTorch 2.7.0 slowed down performance, so the interface uses version 2.4.0 1. PyTorch 2.7.0 降低了性能，因此界面使用 2.4.0 版本 |
3D generation?3D 生成
| Name?名字 | Links?鏈接 | Additional information?其他信息： |
|---|---|---|
| TripoSG?TripoSG 系列 | GitHub - VAST-AI-Research/TripoSG: TripoSG: High-Fidelity 3D Shape Synthesis using Large-Scale Rectified Flow Models | 1. Added custom simple UI. 1. 添加了自定義簡單 UI。 2. Sometimes there are probelms with the preview, but the model should still be available for download. 2. 有時預覽存在問題，但模型仍應可供下載。 |
Tools?工具
| Name?名字 | Links?鏈接 | Additional information?其他信息： |
|---|---|---|
| Fastfetch?快速獲取 | GitHub - fastfetch-cli/fastfetch: A maintained, feature-rich and performance oriented, neofetch like system information tool. | 1. Custom Fastfetch configuration with GPU memory info. 1. 帶有 GPU 內存信息的自定義 Fastfetch 配置。 2. Script supports not only AMD but also NVIDIA graphics cards (nvidia-smi needed). 2. 腳本不僅支持 AMD，還支持 NVIDIA 顯卡（需要 nvidia-smi）。 3. If you change the number or order of graphics cards you must run the installer again. 3. 如果更改了顯卡的數量或順序，則必須再次運行安裝程序。 |
三、Instalation:?安裝方式：
Note?注意
First startup after installation of the selected interface may take longer.
安裝所選接口后首次啟動可能需要更長的時間。
Important?重要
This script does not download any models. If the interface does not have defaults, download your own.
此腳本不會下載任何模型。如果界面沒有默認值，請下載您自己的界面。
Caution?謹慎
If you update, back up your settings and models. Reinstallation deletes the previous directories.
如果您更新，請備份您的設置和模型。重新安裝將刪除以前的目錄。
1. Add the user to the required groups.
1. 將用戶添加到所需的組。
sudo adduser `whoami` video
sudo adduser `whoami` render 2. Reboot?2. 重新啟動
sudo reboot 3. Clone repository?3. 克隆存儲庫
git clone https://github.com/Mateusz-Dera/ROCm-AI-Installer.git 4. Run installer?4. 運行安裝程序
bash ./install.sh 5. Select installation path.
5. 選擇安裝路徑。
6. Select ROCm installation if you are upgrading or running the script for the first time.
6. 如果您是首次升級或運行腳本，請選擇 ROCm 安裝。
7. Install selected interfaces
7. 安裝選定的接口
8. Go to the installation path with the selected interface and run:
8. 轉到包含所選接口的安裝路徑并運行：
./run.sh 軟件下載
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本文信息來源于GitHub作者地址：GitHub - Mateusz-Dera/ROCm-AI-Installer: A script that automatically installs all the required stuff to run selected AI interfaces on AMD Radeon 7900XTX.
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