Instructions to use javawock7618/comfy-wan2.2-workflows with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Wan2.2
How to use javawock7618/comfy-wan2.2-workflows with Wan2.2:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
Wan2.2 GGUF Workflows Collection (with lightx2v LoRA)
This repository provides a collection of highly optimized ComfyUI workflows tailored for the Wan-AI/Wan2.2 model family using GGUF quantized variants. Built completely around ComfyUI's native core nodes and GGUF loaders, these workflows leverage the lightx2v LoRA for accelerated high-speed generation, combined with advanced features such as specific LoRA combinations, motion reference transfer (v2v), and localized detail upscaling while keeping VRAM usage exceptionally low.
Workflow Files & Overview
The repository contains the following production-ready and experimental workflow files.
(Note: YYMM.x in the file names represents the release year, month, and version number, e.g., 2606.1)
| # | File Name | Workflow Target | Key Features & Quick Notes |
|---|---|---|---|
| 1 | Wan2.2(SVI-javanoYYMM.x).json | Image-to-Video (SVI Long Gen) | Long-form video generation using Wan2.2 GGUF sped up by lightx2v LoRA, and stacked with SVI2 Pro LoRA for ultra high-fidelity i2v outputs. |
| 2 | Wan2.2(Anime-javanoYYMM.x).json | Anime / Motion Transfer v2v | Video-to-Video workflow running on GGUF with lightx2v LoRA acceleration that extracts and transfers motion data from reference videos. |
| 3 | Wan2.x(Inpaint-DetailerYYMM.x).json | Localized Inpaint & Detailer | An accelerated GGUF-driven v2v utility designed for partial correction and targeted regional enhancement beyond just the face. |
Detailed Workflow Breakdown
1. Image-to-Video / SVI Long Gen (SVI)
Designed for robust, accelerated long-form video production utilizing Wan2.2's native GGUF Image-to-Video (i2v) architecture.
- Dual LoRA Stacking (lightx2v + SVI2 Pro): Pre-configured to stack the lightx2v LoRA (for fast, few-step sampling) together with the SVI2 Pro LoRA (for structural stability and high-fidelity texturing). This provides a perfect balance between high-speed generation and cinematic realism.
- Extended Sampling Configuration: Features customized temporal scheduling nodes that prevent visual degradation or color bleeding when generating videos beyond standard lengths.
2. Anime / Motion Reference (Anime)
Specialized in traditional Video-to-Video (v2v) conversion utilizing fast GGUF inference and lightx2v acceleration.
- Motion Transfer Engine: Extracts structural motion vectors from a source reference video and projects them onto your new text prompts or initial subject image setup using native core nodes.
- High-Speed Stylization Continuity: Leverages the few-step sampling capability of lightx2v to transform live-action motion into precise anime configurations quickly, while maintaining fluid character tracking across the entire timeline.
3. Localized Inpaint & Detailer (Inpaint-Detailer)
A versatile, fast-rendering Video-to-Video utility built to break the limitations of standard facial-only upscalers.
- Universal Regional Upscaling: Easily isolate and upscale specific, arbitrary regions inside the frame (such as background elements, complex costumes, armor texturing, or hand geometry).
- Targeted Partials & Accelerated Corrections: Driven by lightx2v LoRA for rapid iterations, this advanced native masking sub-graph allows you to partially fix or rewrite prompt items on specified areas (
[Inpaint]) while preserving the surrounding environments without full-frame re-rendering.
Prerequisites & Installation
To ensure all workflows load correctly without errors, please ensure your environment is fully updated:
- ComfyUI Core: Update ComfyUI to v0.24.0 / Frontend 1.45.15 or newer. These workflows run entirely on ComfyUI's native GGUF implementation—no extra model wrapper extensions are needed.
- Custom Nodes:
- Ensure
ComfyUI-GGUF(or the core node equivalent for loading GGUF model weights) and standard utility nodes (such asComfyUI-KJNodes) are fully updated via the ComfyUI Manager. - If any supporting node appears red upon loading, simply use ComfyUI Manager -> Install Missing Custom Nodes.
- Ensure
- Required Assets:
- Base Model (GGUF): Download the correct Wan2.2 GGUF quantized weights and place them into your
models/unet/or designated GGUF directory. - LoRAs:
- lightx2v LoRA is required across all workflows for fast sampling. Place it in your
models/loras/directory. - SVI2 Pro LoRA is additionally required for the
SVIworkflow. Place it in yourmodels/loras/directory.
- lightx2v LoRA is required across all workflows for fast sampling. Place it in your
- Base Model (GGUF): Download the correct Wan2.2 GGUF quantized weights and place them into your
- Downloads last month
- -