# SCAIL 2 Dual-Reference Edit Long Video (Episode 264)
ComfyUI workflow exported from **AI-KSK episode 264**.
**File:** `SCAIL 2 双人参考编辑长视频.json`
## What it does
SCAIL 2 Dual-Reference Edit Long Video. The episode walks through the graph node by node,
explains the model choices, and shows sample outputs.
## How to run
1. Open ComfyUI.
2. Drag `SCAIL 2 双人参考编辑长视频.json` onto the canvas (or *Workflow → Open*).
3. Install any missing nodes the ComfyUI Manager reports.
4. Put the models the graph references into your `models/` folders.
5. Queue the prompt.
Run it without a local GPU on RunningHub:
https://www.runninghub.cn/post/2067260607614767105/?inviteCode=rh-v1111
## Notes
- Tutorial workflow, not a packaged product. Parameters are those used in the episode.
- Model weights are not bundled; each model keeps its own licence.
- Walkthrough video (Chinese): https://youtu.be/mVdLtve8pYA
- Bilibili: https://www.bilibili.com/video/BV1jWL96nEpw/
- Independent AI-KSK release. Not affiliated with or endorsed by the model authors, Comfy Org
or RunningHub.
ComfyUI workflow exported from **AI-KSK episode 264**.
**File:** `SCAIL 2 双人参考编辑长视频.json`
## What it does
SCAIL 2 Dual-Reference Edit Long Video. The episode walks through the graph node by node,
explains the model choices, and shows sample outputs.
## How to run
1. Open ComfyUI.
2. Drag `SCAIL 2 双人参考编辑长视频.json` onto the canvas (or *Workflow → Open*).
3. Install any missing nodes the ComfyUI Manager reports.
4. Put the models the graph references into your `models/` folders.
5. Queue the prompt.
Run it without a local GPU on RunningHub:
https://www.runninghub.cn/post/2067260607614767105/?inviteCode=rh-v1111
## Notes
- Tutorial workflow, not a packaged product. Parameters are those used in the episode.
- Model weights are not bundled; each model keeps its own licence.
- Walkthrough video (Chinese): https://youtu.be/mVdLtve8pYA
- Bilibili: https://www.bilibili.com/video/BV1jWL96nEpw/
- Independent AI-KSK release. Not affiliated with or endorsed by the model authors, Comfy Org
or RunningHub.
Description
# SCAIL 2 Dual-Reference Edit Long Video (Episode 264)
ComfyUI workflow exported from **AI-KSK episode 264**.
**File:** `SCAIL 2 双人参考编辑长视频.json`
## What it does
SCAIL 2 Dual-Reference Edit Long Video. The episode walks through the graph node by node,
explains the model choices, and shows sample outputs.
## How to run
1. Open ComfyUI.
2. Drag `SCAIL 2 双人参考编辑长视频.json` onto the canvas (or *Workflow → Open*).
3. Install any missing nodes the ComfyUI Manager reports.
4. Put the models the graph references into your `models/` folders.
5. Queue the prompt.
Run it without a local GPU on RunningHub:
https://www.runninghub.cn/post/2067260607614767105/?inviteCode=rh-v1111
## Notes
- Tutorial workflow, not a packaged product. Parameters are those used in the episode.
- Model weights are not bundled; each model keeps its own licence.
- Walkthrough video (Chinese): https://youtu.be/mVdLtve8pYA
- Bilibili: https://www.bilibili.com/video/BV1jWL96nEpw/
- Independent AI-KSK release. Not affiliated with or endorsed by the model authors, Comfy Org
or RunningHub.
ComfyUI workflow exported from **AI-KSK episode 264**.
**File:** `SCAIL 2 双人参考编辑长视频.json`
## What it does
SCAIL 2 Dual-Reference Edit Long Video. The episode walks through the graph node by node,
explains the model choices, and shows sample outputs.
## How to run
1. Open ComfyUI.
2. Drag `SCAIL 2 双人参考编辑长视频.json` onto the canvas (or *Workflow → Open*).
3. Install any missing nodes the ComfyUI Manager reports.
4. Put the models the graph references into your `models/` folders.
5. Queue the prompt.
Run it without a local GPU on RunningHub:
https://www.runninghub.cn/post/2067260607614767105/?inviteCode=rh-v1111
## Notes
- Tutorial workflow, not a packaged product. Parameters are those used in the episode.
- Model weights are not bundled; each model keeps its own licence.
- Walkthrough video (Chinese): https://youtu.be/mVdLtve8pYA
- Bilibili: https://www.bilibili.com/video/BV1jWL96nEpw/
- Independent AI-KSK release. Not affiliated with or endorsed by the model authors, Comfy Org
or RunningHub.