This image is exclusively for Runpod templates. It runs Forge-neo and JupyterLab.
9.1K
Stable Diffusion WebUI Forge-neo + JupyterLab, tuned for RunPod with Network Volume support.
š Full guide: https://www.digitalcreativeai.net/en/post/install-webui-forge-neo-runpod-network-volumeā
| Tag | Base | Target GPU |
|---|---|---|
:latest / :cu130 | CUDA 13.0 | RTX 5090 and others |
ā ļø CUDA 13.0 required. In RunPod, click Additional Filters ā CUDA Versions ā select 13.0. CUDA 12.x is NOT supported.
IDLE_TIMEOUT_MINUTES (default 30 min).runpod_api_key ā RUNPOD_API_KEY
TZ=UTC
RUNPOD_API_KEY="{{ RUNPOD_SECRET_API_AutoStop }}"
IDLE_ENABLE=true
IDLE_TIMEOUT_MINUTES=30
JUPYTER_ENABLE=true
AUTO_UPDATE_FORGE=false
IMAGE_CLEAN_ON_START=false
MAX_AGE_HOURS=6
USE_SAGE=true
FORGE_ARGS=--api --theme dark --disable-safe-unpickle --enable-insecure-extension-access --uv --sage
Port Service 7860 Forge-neo 8888 JupyterLab (if enabled)
~20 minutes. SageAttention is built automatically for your GPU.
āā forge/
ā āā sd-webui-forge-neo/
ā āā venv/ (Python 3.13)
ā āā models/
āā outputs/
| Flag | Effect | Requires |
|---|---|---|
| --sage | SageAttention | USE_SAGE=true |
| --flash | Flash Attention | ā |
| --cuda-malloc | Async CUDA malloc | ā |
| --nunchaku | Nunchaku SVDQ models | ā |
Backup: run forge-backup in terminal ā saved to /workspace/outputs, restored on next launch.
Auth: set FORGE_USERNAME / FORGE_PASSWORD to enable Gradio login.
Content type
Image
Digest
sha256:7c503b4c5ā¦
Size
4.2 GB
Last updated
4 months ago
docker pull dcainet/forge-neo-min