---
title: Sapsan-VFI
canonical_url: "https://www.modelscope.cn/models/SnJake/Sapsan-VFI"
md_url: "https://www.modelscope.cn/models/SnJake/Sapsan-VFI.md"
repository: SnJake/Sapsan-VFI
last_updated: 2026-02-09
license: mit
architectures:
  - SapsanVFI
parameters: 54.1M
tensor_type:
  - F32
library_name:
  - safetensors
  - pytorch
frameworks:
  - pytorch
downloads: 33
stars: 0
tags:
  - computer-vision
  - video
  - video-frame-interpolation
  - vfi
  - video-to-video
  - comfyui
  - pytorch
---

# Sapsan-VFI

> Sapsan-VFI - SnJake 在 ModelScope 开源的模型。Sapsan-VFI is a x2 frame interpolation model for video. It inserts a single middle frame between every input pair, effectively doubling the FPS.

SnJake/Sapsan-VFI 是 ModelScope 魔搭社区上的 54.1M 参数机器学习模型，采用 mit 许可。

- **Repository**: SnJake/Sapsan-VFI
- **License**: mit
- **Parameters**: 54.1M
- **Tags**: computer-vision, video, video-frame-interpolation, vfi, video-to-video, comfyui, pytorch
- **Downloads**: 33
- **Stars**: 0
- **Last updated**: 2026-02-09

Source: https://www.modelscope.cn/models/SnJake/Sapsan-VFI

---

# SnJake Sapsan-VFI

Sapsan-VFI is a **x2 frame interpolation** model for video. It inserts a single middle frame between every input pair, effectively doubling the FPS.

## Examples

<video controls autoplay loop muted playsinline src="https://huggingface.co/SnJake/Sapsan-VFI/resolve/main/videos/1_comparison_x2.mp4" width="100%"></video>

<video controls autoplay loop muted playsinline src="https://huggingface.co/SnJake/Sapsan-VFI/resolve/main/videos/2_comparison_x2.mp4" width="100%"></video>

<video controls autoplay loop muted playsinline src="https://huggingface.co/SnJake/Sapsan-VFI/resolve/main/videos/3_comparison_x2.mp4" width="100%"></video>

## How to use in ComfyUI

The model is designed to work with the **Sapsan-VFI** ComfyUI node.

1. Install the node from the [GitHub repo](https://github.com/SnJake/SnJake_Sapsan-VFI).
2. Download the weights from this repository.
3. Place the file(s) into `ComfyUI/models/sapsan_vfi/`.
4. Select the weights in the node dropdown and run the workflow.

Recommended workflow:

Example workflow can be found in `Example Workflow` folder in [GitHub repo](https://github.com/SnJake/SnJake_Sapsan-VFI).


Notes:
- The node has a `console_progress` toggle to print progress in the ComfyUI console.

## Weights

- `Sapsan-VFI.safetensors`
- `Sapsan-VFI.pt`

## Training Details

- Created out of curiosity and personal interest.
- Total epochs: **11**
- Dataset: **2700 videos**
- Shards: **151** shards of **1000** shadrs in each. 151 000 triplets.

Training code is included in `training_code/` for reference.

## Disclaimer

This project was made purely for curiosity and personal interest. The code was written by GPT-5.2 Codex.