diff --git a/nodes_model_loading.py b/nodes_model_loading.py index f37ef1e..77e68cb 100644 --- a/nodes_model_loading.py +++ b/nodes_model_loading.py @@ -344,7 +344,7 @@ class WanVideoLoraSelect: "optional": { "prev_lora":("WANVIDLORA", {"default": None, "tooltip": "For loading multiple LoRAs"}), "blocks":("SELECTEDBLOCKS", ), - "low_mem_load": ("BOOLEAN", {"default": False, "tooltip": "Load the LORA model with less VRAM usage, slower loading. This affects ALL LoRAs, not just the current one"}), + "low_mem_load": ("BOOLEAN", {"default": False, "tooltip": "Load the LORA model with less VRAM usage, slower loading. This affects ALL LoRAs, not just the current one. No effect if merge_loras is False"}), "merge_loras": ("BOOLEAN", {"default": True, "tooltip": "Merge LoRAs into the model, otherwise they are loaded on the fly. Always enabled for GGUF and scaled fp8 models. This affects ALL LoRAs, not just the current one"}), }, "hidden": { @@ -359,6 +359,8 @@ class WanVideoLoraSelect: DESCRIPTION = "Select a LoRA model from ComfyUI/models/loras" def getlorapath(self, lora, strength, unique_id, blocks={}, prev_lora=None, low_mem_load=False, merge_loras=True): + if not merge_loras: + low_mem_load = False # Unmerged LoRAs don't need low_mem_load loras_list = [] strength = round(strength, 4) @@ -447,7 +449,7 @@ class WanVideoLoraSelectMulti: "optional": { "prev_lora":("WANVIDLORA", {"default": None, "tooltip": "For loading multiple LoRAs"}), "blocks":("SELECTEDBLOCKS", ), - "low_mem_load": ("BOOLEAN", {"default": False, "tooltip": "Load the LORA model with less VRAM usage, slower loading"}), + "low_mem_load": ("BOOLEAN", {"default": False, "tooltip": "Load the LORA model with less VRAM usage, slower loading. No effect if merge_loras is False"}), "merge_loras": ("BOOLEAN", {"default": True, "tooltip": "Merge LoRAs into the model, otherwise they are loaded on the fly. Always enabled for GGUF and scaled fp8 models. This affects ALL LoRAs, not just the current one"}), } @@ -462,6 +464,8 @@ class WanVideoLoraSelectMulti: def getlorapath(self, lora_0, strength_0, lora_1, strength_1, lora_2, strength_2, lora_3, strength_3, lora_4, strength_4, blocks={}, prev_lora=None, low_mem_load=False, merge_loras=True): + if not merge_loras: + low_mem_load = False # Unmerged LoRAs don't need low_mem_load loras_list = list(prev_lora) if prev_lora else [] lora_inputs = [ (lora_0, strength_0),