LoRA Pipeline
Layers non-fused LoRA adapters on top of an existing pipeline so the same cached model can power multiple branches simultaneously.
Category: ModularDiffusion/Pipeline
TL;DR
- Connect a Pipeline Builder output and one or more Load LoRA nodes here; wire the
lora_pipelineoutput to Generate Media Latents instead of the Pipeline Builder directly. - Adapters are activated per generation and released afterward — the base pipeline is never permanently modified, so a single cached model can drive multiple branches (one with LoRAs, one without) without rebuilding.
- Prefer this node over fusing LoRAs on the Pipeline Builder when swapping adapters between runs or using in-context (IC) LoRAs, distillation/acceleration LoRAs, or slider LoRAs.
Typical workflow position
Pipeline Builder ──→ [LoRA Pipeline] ←── Load LoRA
│
└──→ Generate Media Latents → Decode Media Latent
Node preview

Inputs
| Name | Type | Required | Notes |
|---|---|---|---|
pipeline |
Pipeline Config |
Yes | Base diffusion pipeline. Connect from Pipeline Builder. The base pipeline is reused, not modified — wire it to other nodes simultaneously. |
loras |
loras |
Yes | One or more LoRA payloads from Load LoRA nodes. Accepts a list; connect multiple Load LoRA outputs to stack adapters. |
Outputs
| Name | Type | Notes |
|---|---|---|
lora_pipeline |
Pipeline Config |
Pipeline reference that activates the listed LoRAs around each generation call. Shares the cache entry of the input pipeline — wiring this to Generate Media Latents does not trigger a rebuild. |
logs |
str | Build log, including the pipeline configuration hash. |
Tips & pitfalls
- Activation LoRAs vs. fused LoRAs are not equivalent. Fused LoRAs (baked via the Pipeline Builder
lorasinput) are permanently merged into weights; activation LoRAs (this node) are applied transiently. Changing a fused LoRA evicts the entire pipeline cache. Changing an activation LoRA does not. - Connect at least one LoRA. The node requires at least one entry in
lorasto activate — wire one or more Load LoRA nodes before running. - The
lora_pipelineoutput shares the cache with the inputpipeline. You can wire both to separate Generate Media Latents nodes (one with LoRAs, one without) without loading the model twice. - LoRA weights are applied per run. Unlike fused LoRAs, changing
weighton a Load LoRA node between runs does not rebuild the pipeline.
See also
- Load LoRA — provides the
lorasinput. - Modular Diffusion Pipeline Builder — provides the base
pipelineinput. - Generate Media Latents — consumes the
lora_pipelineoutput.