📥 Lora Download

Most LoRA loaders assume the file is already on your disk. This one doesn't - it takes a download URL, fetches the LoRA, and applies it to your model and CLIP in the same node, with the usual strength dials. So instead of "download the LoRA, drop it in the folder, restart, then add a LoRA loader," it's one node in your graph. Handy when you're chasing a specific LoRA off Civitai and want it wired in immediately.

What it's doing

A LoRA is a small patch that nudges a model toward a style, character, or concept without retraining the whole thing - you stack it on top of a checkpoint and it adjusts how the model denoises. Applying one means modifying both the diffusion model and the CLIP text encoder, which is why this node takes a model and a clip as inputs and returns modified versions of both. Same contract as ComfyUI's stock LoRA loader; the only twist is the download step in front.

The inputs and outputs that matter

• model and clip - the model and CLIP you're patching. Pipe these in from your checkpoint loader. The LoRA modifies both and passes them on.
• Download_url - a Civitai or Hugging Face link to the LoRA.
• Lora_url_name - the filename to save as, e.g. add_detail.safetensors. Rename from the default so your loras folder stays legible.
• strength_model (default 1.0) - how hard the LoRA pushes the diffusion model. This is the dial you actually reach for. 0.6–0.8 is a common sane range; crank it past 1.0 and things start to fry.
• strength_clip (default 1.0) - how hard it pushes the text encoder. Most people leave it at 1.0 or match it to strength_model.

Outputs are the patched MODEL and CLIP. Chain multiple of these to stack LoRAs - the README explicitly supports combining several LoRA nodes in a row.

Installing it

ComfyUI Manager: search SDVN_Comfy_node, install, restart. Manual:

cd ComfyUI/custom_nodes
git clone https://github.com/StableDiffusionVN/SDVN_Comfy_node

Then pip install -r custom_nodes/SDVN_Comfy_node/requirements.txt from your ComfyUI root, and restart. Windows/macOS need aria2c installed for the download.

Where people get burned

Base-model mismatch. A LoRA trained on SD 1.5 won't do anything useful on an SDXL model, and neither loads on Flux. LoRAs are architecture-specific - download the one built for the base you're running. If a LoRA "does nothing," this is the first thing to check.

Overcranking strength. strength_model at 1.5+ is where images start to burn, oversaturate, or collapse into the LoRA's training artifacts. If the effect is too weak, it's tempting to just crank it - but often the fix is a better-trigger prompt, not more strength. Back off to 0.7 and add the LoRA's trigger words.

Stacking too many. Chaining LoRA nodes works, but every LoRA you stack competes for influence, and three or four strong ones fighting each other gives you mud. Fewer, well-tuned LoRAs beat a tall stack.

Download failed. Missing aria2c on Windows/macOS, or a Civitai link that needs an API key. The console logs the attempt.