Add a TomePatchModel node to the _for_testing section.

Tome increases sampling speed at the expense of quality.

nodes.py

@@ -254,6 +254,22 @@ class LoraLoader:
         model_lora, clip_lora = comfy.sd.load_lora_for_models(model, clip, lora_path, strength_model, strength_clip)
         return (model_lora, clip_lora)
 
+class TomePatchModel:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {"required": { "model": ("MODEL",),
+                              "ratio": ("FLOAT", {"default": 0.3, "min": 0.0, "max": 1.0, "step": 0.01}),
+                              }}
+    RETURN_TYPES = ("MODEL",)
+    FUNCTION = "patch"
+
+    CATEGORY = "_for_testing"
+
+    def patch(self, model, ratio):
+        m = model.clone()
+        m.set_model_tomesd(ratio)
+        return (m, )
+
 class VAELoader:
     @classmethod
     def INPUT_TYPES(s):
@@ -646,7 +662,7 @@ def common_ksampler(model, seed, steps, cfg, sampler_name, scheduler, positive,
     model_management.load_controlnet_gpu(control_net_models)
 
     if sampler_name in comfy.samplers.KSampler.SAMPLERS:
-        sampler = comfy.samplers.KSampler(real_model, steps=steps, device=device, sampler=sampler_name, scheduler=scheduler, denoise=denoise)
+        sampler = comfy.samplers.KSampler(real_model, steps=steps, device=device, sampler=sampler_name, scheduler=scheduler, denoise=denoise, model_options=model.model_options)
     else:
         #other samplers
         pass
@@ -1016,6 +1032,7 @@ NODE_CLASS_MAPPINGS = {
     "CLIPVisionLoader": CLIPVisionLoader,
     "VAEDecodeTiled": VAEDecodeTiled,
     "VAEEncodeTiled": VAEEncodeTiled,
+    "TomePatchModel": TomePatchModel,
 }
 
 def load_custom_node(module_path):