---
title: Wan 2.2 I2V 14B · Custom lora + CivitAI
emoji: 🎬
colorFrom: indigo
colorTo: pink
sdk: gradio
sdk_version: 6.24.0
app_file: app.py
pinned: true
short_description: Image to video, your lora + CivitAI, stitching, cost readout
tags:
  - video
  - image-to-video
  - wan
  - wan2.2
  - lora
  - civitai
  - zerogpu
---

# Wan 2.2 I2V 14B · Custom lora

Turn a still image into smooth cinematic motion, with your own adapters and without guessing what a
run will cost.

## What is in here

**Your own lora, from anywhere.** Five slots that take a Hugging Face repo, a file inside one, or a
**CivitAI download link** pasted straight into the High or Low box. Wan adapters ship their two
halves as separate files, so each slot has one box for each. Downloads are cached, and a gated
CivitAI model works once `CIVITAI_TOKEN` is set under *Settings → Variables and secrets* — the Space
downloads on its own machine, so a browser session on CivitAI does not authenticate it.

**Built-in lora.** Three preset slots drawing on a curated catalogue, each with its own high and low
strength.

**Fast options.** Speed presets that set the steps, the flow shift and the scheduler in one click,
including the lightx2v Lightning adapters at 4, 6 and 8 steps. The checkpoint is a Lightning merge
already, so *Built-in* is the place to start.

**ZeroGPU cost, before you press the button.** The readout above Generate uses the very formula the
Space reserves with, so heavy settings are visible as a number rather than as a failed run.

**Clip stitching and looping, on the CPU.** Queue several clips and they are joined into one file;
tick the box and every new generation joins on its own. Boomerang loops the whole clip or just its
tail. None of it touches the GPU allowance.

**Named profiles.** Save a whole set-up under a name and bring it back from a dropdown, or export it
as `.json`.

**Frame grabbing.** Pause the result on any frame and send it to the start image or the end image,
so a scene can continue from where it stopped.

## Notes

* fp8 quantized, AoT compiled, with RIFE interpolation for smoother motion.
* Longer clips reserve more ZeroGPU time; the cost line tells you how much.
* Profiles live inside the Space. With persistent storage attached they survive a restart, and they
  are visible to everyone who opens the Space.

Configuration reference: https://huggingface.co/docs/hub/spaces-config-reference