Nodes/was-node-suite-comfyui/Diffusers Model Loader
ComfyUI Node Runs on cloud

Diffusers Model Loader

Load a HuggingFace diffusers model you've already downloaded

By WASasquatch·Created 3 years ago·Updated a day ago· 1,839
Diffusers Model Loader
    • MODEL
    • CLIP
    • VAE
    • NAME_STRING
    model_path

    This is the quieter sibling of Diffusers Hub Model Down-Loader - same underlying idea, no download step. Where that node fetches a model from HuggingFace by repo ID, Diffusers Model Loader points at a diffusers-format model you've already got sitting on disk (cloned manually, downloaded earlier, or exported from a training run) and just loads it. If you're re-running the same model repeatedly, or you're offline, or you'd rather manage the download yourself, this is the one you want instead.

    Why "diffusers format" is the detail that matters

    HuggingFace's diffusers library expects models laid out as a pipeline folder - separate subfolders for the UNet, text encoder(s), VAE, and scheduler config, plus a model_index.json tying it together - not the single .safetensors file most ComfyUI checkpoints ship as. WAS built its own path for loading that layout directly, which is why this exists as a distinct node rather than something the standard checkpoint loader handles. If a model you want is only distributed in that multi-file diffusers layout, this is how you get it into a WAS graph without hand-converting it first.

    How it works

    You give it a local path to a diffusers-format model directory, and it loads that pipeline into memory for downstream WAS nodes to use. It doesn't fetch anything from the network - that's the entire difference from its Hub-downloading sibling. Because the object it produces isn't ComfyUI's native MODEL/CLIP/VAE triple, it's meant to feed WAS's own diffusers-aware nodes rather than a standard KSampler chain built for checkpoint-loaded models.

    When you'd reach for this over the Hub loader

    Anytime the model's already on your machine and you don't want to re-download it every session, or you're working somewhere without reliable network access to HuggingFace, or you manage your model downloads separately (a shared model drive, a script, whatever) and just need ComfyUI to pick up what's already there.

    How to install it

    ComfyUI Manager: search "WAS Node Suite," install, restart. Manual:

    cd ComfyUI/custom_nodes
    git clone https://github.com/WASasquatch/was-node-suite-comfyui
    

    then install requirements from inside that folder - path/to/ComfyUI/python_embeded/python.exe -s -m pip install -r requirements.txt on portable, pip install -r requirements.txt on system Python. Restart ComfyUI; find it under WAS Suite.

    Common issues & troubleshooting

    The most likely failure is a path or layout problem, not a bug in the node: if the folder you point it at isn't a genuine diffusers pipeline directory (missing model_index.json, or it's actually just a loose .safetensors file), loading will fail. Make sure whatever you downloaded is the full diffusers export, not a single-file conversion - those need the standard checkpoint loader instead, not this node.

    Beyond that, this inherits the pack's general risk profile: WAS Node Suite has had no active development since it was marked retired in December 2023, and a loader built against a particular version of the diffusers library is exactly the kind of thing that can quietly break as that library moves on, with nobody upstream chasing the fix. If the whole suite goes "Import Failed" after a ComfyUI update, that's usually a dependency version clash rather than anything about this specific node - re-running the requirements install with your embedded Python interpreter (not a system one) is the fix that's actually worked for people stuck on it.

    CategoryWAS Suite/Loaders

    Inputs (1)

    NameTypeDefaultDescription
    model_pathCOMBOThe model directory in models/diffusers to load. Each entry is a folder holding unet, vae and text_encoder subdirectories, which is what cloning a Hugging Face model repository produces.

    Outputs (4)

    NameTypeDescription
    MODELMODELThe diffusion model, for a sampler.
    CLIPCLIPThe text encoder, for the prompt encoding nodes.
    VAEVAEThe autoencoder that turns a latent into an image.
    NAME_STRINGSTRINGThe name of the directory the model was loaded from, for captions, file names and log lines.