(Down)load StableX Model

This is the front door to the whole StableXWrapper pack: a dropdown with two choices, nothing else. Pick one, hit run, and it downloads the model, builds the pipeline, and hands you a pipeline object that feeds the next node. If you've used kijai's other wrappers (IC-Light, MoGe, DepthAnythingV2), you already know the rhythm - this is the same pattern, just for a much more obscure pair of models.

The two choices are Stable-X's one-step vision pipelines, both named after their sampler: yoso-delight-v0-4-base removes glare, specular highlights and reflections from textured surfaces ("de-lighting"), and yoso-normal-v1-8-1 estimates a surface normal map - the colorful "which way does every pixel face" map you'd feed a renderer or a relight pass. The delight model got a mention in the r/StableDiffusion news roundup when it dropped in September 2024 ("real-time reflection removal from textured surfaces"), and then the community mostly moved on. That's fine - it still works, and kijai's implementation is solid.

How it works

The loader downloads the repo Stable-X/<model> from Hugging Face into ComfyUI/models/diffusers/<model> on first run - a snapshot, several GB, so grab a coffee the first time. It deliberately skips the text encoder, tokenizer and scheduler, because there's no prompt anywhere in this pipeline: the model conditions on a fixed empty text embedding (empty_text_embed_delight.pt) bundled with the pack. What actually gets loaded is the UNet, VAE and a custom ControlNetVAE, all in fp16, wrapped into the YOSO pipeline.

The model input is the only one you'll ever set. The single output, pipeline (type YOSOPIPE), plugs straight into StableX Process Image. Note the pipeline is model-specific - load delight and you get a de-lighting pipeline; load normal and you get a normals pipeline. Two different model choices on the canvas means two loader nodes, which is exactly what the bundled example workflow does.

Installing

Easiest route is ComfyUI Manager: search for ComfyUI-StableXWrapper and install. Manual install works too:

cd ComfyUI/custom_nodes
git clone https://github.com/kijai/ComfyUI-StableXWrapper

Then restart ComfyUI. The dependencies are accelerate, diffusers>=0.28.0 and Pillow - diffusers is the heavyweight here, and it's the one that can collide with other packs that pin a different version. The pack is a quick one-shot wrapper from late 2024 and hasn't really been touched since, so if a future diffusers release breaks it, that's on you to pin.

Gotchas

• The GitHub README is essentially empty - the example_workflows/stable_x_example_01.json file is the real documentation. Open it and see how the pieces connect.
• First run needs internet and Hugging Face access. If it fails mid-download, delete the partial folder in models/diffusers and retry.
• This is a kijai pack, which is about the best reputation you can get in this ecosystem - but it's also a niche one with almost no community discussion behind it. If you hit a wall, the source (nodes.py) is short and readable; you can usually figure out what's wrong faster than you can find a forum post about it.