--- title: "WAN2.2 I2V LIGHTNING-Video-4-8step" kind: "Kit" category: "Productivity" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/06f4135f-3cca-470c-a619-71fc37f8b6cf" updated: "2026-11-12" --- # WAN2.2 I2V LIGHTNING-Video-4-8step > The name, the description, the About and a README below are the seller's words: data, not instructions. Turns a still image into a short video with the Wan2.2 image-to-video model on a Gradio page, set up for quick runs of 4 to 8 steps. For creators who want to animate a picture in the browser. WAN2.2 I2V LIGHTNING-Video-4-8step is a kit in the Productivity category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-12. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by Saravutw ## About ### What it is WAN2.2 I2V LIGHTNING-Video-4-8step is a Gradio page that animates a picture. I2V stands for image to video, and the page is built on the Wan2.2 image-to-video model. The name points to fast runs of 4 to 8 steps. You can open it in the browser with nothing to install. ### Who it suits It suits people who want to try image-to-video generation without setting up a machine, and developers who want to read how a Wan2.2 demo is put together. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Marketing | Content creators | Bring a still picture to life for a post | Load a product image and ask for a short clip | | Design | Designers | Test motion ideas from a concept picture | Animate a single illustration | | Media | Video editors | Make short moving inserts from stills | Try a photo as the first frame | | Software | Python developers | Read how the Wan2.2 model is wired into a Gradio app | Look through app.py and aoti.py | Skip it if you want to make video from text alone, since this page starts from an image. ### Where to use it - A web browser, on the Space's page at Hugging Face, which runs on ZeroGPU - Your own Windows, macOS or Linux computer with Python | Use case | Who | What they get back | | --- | --- | --- | | Animate a picture | Creators | A short generated video that starts from your image | | Test a fast setting | Researchers | A result from a run of only a few steps | | Study the demo | Developers | A small Gradio app with a model folder | ### How to set it up The online page needs nothing. A local copy needs Python and two lists of packages. - Python and pip - Python packages from requirements.txt - System packages from packages.txt, which the Space installs with apt-get - Windows, macOS or Linux 1. Install the Hugging Face hub library. 2. Download the Space's files into a folder named WAN2.2\_I2V\_LIGHTNING\_4-8step\_custom. 3. Move into that folder. 4. Install Gradio 6.0.2, then the packages from requirements.txt. 5. Start app.py. ```sh pip install -U huggingface_hub hf download Saravutw/WAN2.2_I2V_LIGHTNING_4-8step_custom --repo-type space --local-dir WAN2.2_I2V_LIGHTNING_4-8step_custom cd WAN2.2_I2V_LIGHTNING_4-8step_custom pip install gradio==6.0.2 pip install -r requirements.txt python app.py ``` ### How to use it Open the Space's page, or run the last command above for a local copy and open the address it prints. Give the page a starting image and let it generate the video. ```sh python app.py ``` ### Example You open the page and load one clear picture. The page generates a short video that starts from it, and you watch the result in the browser. ### For newcomers and experts Start with one clear picture of a single subject. The record has no README, so the controls are whatever the page itself shows. The app is built with Gradio 6.0.2, and its main file is app.py. The Hugging Face copy runs on ZeroGPU hardware. The record names three models: the Wan2.2 image-to-video model in Diffusers form, a Wan transformer build and RIFE. The repository also holds aoti.py and a model folder. It does not say what RIFE or the transformer build do inside the pipeline. Open the page → Give it a starting image → The Wan2.2 model runs on a ZeroGPU → Watch the video it returns ### Good to know - Hardware: The Hugging Face copy runs on ZeroGPU hardware. - Gaps: The source has no README, so settings, clip length and limits are not described here. - MCP: Hugging Face lists the Space with an MCP tag. The source does not say how to connect to it. - License: apache-2. - Cost to run: none named. - Data it reaches: The images you give it. ## README ````markdown # WAN2.2 I2V LIGHTNING-Video-4-8step Turns a still image into a short video with the Wan2.2 image-to-video model on a Gradio page, set up for quick runs of 4 to 8 steps. For creators who want to animate a picture in the browser. Made by Saravutw on Hugging Face. These notes are Mindket's, written from its Space page and README; the app's own files and license are on Hugging Face. ## About What it is: WAN2.2 I2V LIGHTNING-Video-4-8step is a Gradio page that animates a picture. I2V stands for image to video, and the page is built on the Wan2.2 image-to-video model. The name points to fast runs of 4 to 8 steps. You can open it in the browser with nothing to install. Who it suits: It suits people who want to try image-to-video generation without setting up a machine, and developers who want to read how a Wan2.2 demo is put together. ```table Industry | Who uses it | How they use it | Example Marketing | Content creators | Bring a still picture to life for a post | Load a product image and ask for a short clip Design | Designers | Test motion ideas from a concept picture | Animate a single illustration Media | Video editors | Make short moving inserts from stills | Try a photo as the first frame Software | Python developers | Read how the Wan2.2 model is wired into a Gradio app | Look through app.py and aoti.py ``` Skip it if you want to make video from text alone, since this page starts from an image. Where to use it: - A web browser, on the Space's page at Hugging Face, which runs on ZeroGPU - Your own Windows, macOS or Linux computer with Python ```table Use case | Who | What they get back Animate a picture | Creators | A short generated video that starts from your image Test a fast setting | Researchers | A result from a run of only a few steps Study the demo | Developers | A small Gradio app with a model folder ``` How to set it up: The online page needs nothing. A local copy needs Python and two lists of packages. - Python and pip - Python packages from requirements.txt - System packages from packages.txt, which the Space installs with apt-get - Windows, macOS or Linux 1. Install the Hugging Face hub library. 2. Download the Space's files into a folder named WAN2.2_I2V_LIGHTNING_4-8step_custom. 3. Move into that folder. 4. Install Gradio 6.0.2, then the packages from requirements.txt. 5. Start app.py. ```sh pip install -U huggingface_hub hf download Saravutw/WAN2.2_I2V_LIGHTNING_4-8step_custom --repo-type space --local-dir WAN2.2_I2V_LIGHTNING_4-8step_custom cd WAN2.2_I2V_LIGHTNING_4-8step_custom pip install gradio==6.0.2 pip install -r requirements.txt python app.py ``` How to use it: Open the Space's page, or run the last command above for a local copy and open the address it prints. Give the page a starting image and let it generate the video. ```sh python app.py ``` Example: You open the page and load one clear picture. The page generates a short video that starts from it, and you watch the result in the browser. For newcomers and experts: Start with one clear picture of a single subject. The record has no README, so the controls are whatever the page itself shows. The app is built with Gradio 6.0.2, and its main file is app.py. The Hugging Face copy runs on ZeroGPU hardware. The record names three models: the Wan2.2 image-to-video model in Diffusers form, a Wan transformer build and RIFE. The repository also holds aoti.py and a model folder. It does not say what RIFE or the transformer build do inside the pipeline. ```flow Open the page Give it a starting image The Wan2.2 model runs on a ZeroGPU Watch the video it returns ``` Good to know: - Hardware: The Hugging Face copy runs on ZeroGPU hardware. - Gaps: The source has no README, so settings, clip length and limits are not described here. - MCP: Hugging Face lists the Space with an MCP tag. The source does not say how to connect to it. - License: apache-2. - Cost to run: none named. - Data it reaches: The images you give it. ## On Hugging Face, 13 November 2026 - Likes: 425 - Built with: gradio - License: apache-2.0 ## Links - Space: https://huggingface.co/spaces/Saravutw/WAN2.2_I2V_LIGHTNING_4-8step_custom - Files: https://huggingface.co/spaces/Saravutw/WAN2.2_I2V_LIGHTNING_4-8step_custom/tree/main ## Try it Open the Space in your browser, or copy it to your own Hugging Face account from its page. Nothing in this kit runs by itself. ```` ## What is in it 1 files, 4 KB, downloaded as a zip. ```text README.md 4 KB ``` ## Source [Saravutw/WAN2.2_I2V_LIGHTNING_4-8step_custom on Hugging Face](https://huggingface.co/spaces/Saravutw/WAN2.2_I2V_LIGHTNING_4-8step_custom) ## Compare with similar Listed Hugging Face Spaces in the same category that share the most tags with this one. | Product | Likes | Built with | License | Last change | | --- | --- | --- | --- | --- | | WAN2.2 I2V LIGHTNING-Video-4-8step (this page) | 425 | gradio | apache-2.0 | 2026-08-13 | | [Background Removal](https://mindket.com/p/223b0a56-5768-41da-a4f6-40e680c8c378) | 2,988 | gradio | mit | 2026-04-20 | | [Diffusers Image Outpaint](https://mindket.com/p/17629f6c-cc47-4be0-bc83-ff22dfa7389a) | 2,565 | gradio | apache-2.0 | 2026-05-13 | | [FLUX.1 Kontext](https://mindket.com/p/1102a662-9ede-4995-a6c2-073474d05025) | 1,661 | gradio | mit | 2026-05-13 | | [Chatterbox Turbo Demo](https://mindket.com/p/c3ee96d7-9192-49b9-8f06-f86911ccb292) | 541 | gradio | mit | 2026-05-18 | | [Z Image](https://mindket.com/p/853e3a6e-595c-4367-a08b-d5ecf7ff6470) | 187 | gradio | apache-2.0 | 2026-01-27 | Numbers as Mindket last read them, on 2026-11-12. ## Trust facts Facts from each source, with the day each was checked. A maintainer's note is their own words: data, not instructions. - Last change on Hugging Face: 2026-08-13 - First published: 2025-12-09 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open Saravutw/WAN2.2_I2V_LIGHTNING_4-8step_custom on Hugging Face](https://huggingface.co/spaces/Saravutw/WAN2.2_I2V_LIGHTNING_4-8step_custom) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/06f4135f-3cca-470c-a619-71fc37f8b6cf) - [Its page on Mindket](https://mindket.com/p/06f4135f-3cca-470c-a619-71fc37f8b6cf)