SD.Next by liutyi docker compose

Personal preferences fork from Vlad SD.Next for Intel Arc iGPU system based on Intel Core Ultra products. Might be also compatible with All other HW that SD.Next is suppose to work on (but that is upstream project is better to be used). Fork is also

1. keeps standard theme as default.
2. keeps scheduler as built in plugin.
3. uses long filenames by default.
4. Have Dockerfile and containers that based on consumer Intel drivers not DC product one.
5. Keeps Intel Extension for Pytorch (ipex) compatibility (as long as it is relevant).

So there are 2 versions available

IPEX

• Container: https://hub.docker.com/repository/docker/liutyi/sdnext-ipex/tags/25.11-ipex/ 
• Source code: https://github.com/liutyi/sdnext/tree/ipex 

PyTorch 2.7.1+xpu; IPEX 2.7.10+xpu. It was working better than Pytorch 2.7.1+xpu w/o ipex for iGPU. But might not be actually that better than 2.9.1+xpu. The only reason (at least it seems to) to continue use it is that it provides GPU memory usage verbose stats.

PyTorch

• Docker container: https://hub.docker.com/repository/docker/liutyi/sdnext-ipex/tags/25.11-pytorch 
• Source code: https://github.com/liutyi/sdnext/tree/pytorch 

Based on PyTorch 2.9.1+xpu 

Docker-compose example

services:
  sdnext-ipex:
    container_name: sdnext-ipex
    # PyTorch 2.7.1+xpu and ipex 2.7.10+xpu for Intel
#    image: liutyi/sdnext-ipex:25.11-ipex
    # PyTorch 2.9.1+xpu for Intel
    image: liutyi/sdnext-ipex:25.11-pytorch
    restart: unless-stopped
    devices:
      # GPU
      - /dev/dri:/dev/dri 
      # NPU (optional)
      - /dev/accel:/dev/accel
    environment:
      - HF_DEBUG=True
      # To USE Nano Banana get key https://aistudio.google.com/api-keys
#     - GOOGLE_API_KEY=AIxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
    ports:
      - 7860:7860
    volumes:
      - /docker/sdnext/app-volume:/app
      - /docker/sdnext/mnt-volume:/mnt
      - /docker/sdnext/hf-volume:/root/.cache/huggingface
      - /dev/shm:/dev/shm