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tenser-tensor-ComfyUI-Tense…/web/docs/TT_SdxlModelsLoaderAdvanced.md
T
TenserTensor 3a0b6bd856 Add SDXL model loaders with documentation
Implement SDXL loading nodes:
- sdxl_models_loader.py: basic all-in-one loader with checkpoint merging
- sdxl_models_loader_advanced.py: extended loader with 4 LoRA slots and advanced VAE/CLIP settings

Add markdown documentation for both nodes
2026-02-13 16:32:12 +03:00

3.0 KiB

TT_SdxlModelsLoaderAdvanced

Extended all-in-one model loader for SDXL with checkpoint merging and LoRA support.

Inputs

Parameter Type Required Description
primary_ckpt CHECKPOINT Yes Primary SDXL checkpoint to load
secondary_ckpt CHECKPOINT Yes Secondary checkpoint to merge (select "None" to skip)
primary_weight FLOAT Yes Weight for primary checkpoint in merge (0.0-1.0, default: 1.0)
clip_l TEXT_ENCODER Yes CLIP-L text encoder model
clip_g TEXT_ENCODER Yes CLIP-G text encoder model
clip_device STRING Yes Device for CLIP ("default" or "cpu") - advanced
lora_name_1 LORA Yes First LoRA to apply (select "None" to skip)
strength_1 FLOAT Yes Strength for first LoRA (-10.0 to 10.0, default: 1.0)
lora_name_2 LORA Yes Second LoRA to apply (select "None" to skip)
strength_2 FLOAT Yes Strength for second LoRA (-10.0 to 10.0, default: 1.0)
lora_name_3 LORA Yes Third LoRA to apply (select "None" to skip)
strength_3 FLOAT Yes Strength for third LoRA (-10.0 to 10.0, default: 1.0)
lora_name_4 LORA Yes Fourth LoRA to apply (select "None" to skip)
strength_4 FLOAT Yes Strength for fourth LoRA (-10.0 to 10.0, default: 1.0)
vae_name VAE Yes VAE model to load
vae_device STRING Yes Device for VAE ("default" or "cpu") - advanced
vae_dtype STRING Yes Data type for VAE ("bfloat16", "float16", "float32") - advanced

Outputs

Parameter Type Description
MODEL MODEL Loaded model with applied LoRAs and optional merge
CLIP CLIP Combined CLIP-L and CLIP-G text encoders with applied LoRAs
VAE VAE Loaded VAE

Usage

Extended version of the SDXL loader with support for up to 4 LoRAs and additional VAE configuration options. Load all model components, optionally merge checkpoints, apply LoRAs sequentially, and configure device/dtype settings for CLIP and VAE. LoRAs are cached for efficiency.


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