diff --git a/src/custom_schedulers/get_sigmas_sigmoid.py b/src/custom_schedulers/get_sigmas_sigmoid.py
index 6fdd64d..9d64454 100644
--- a/src/custom_schedulers/get_sigmas_sigmoid.py
+++ b/src/custom_schedulers/get_sigmas_sigmoid.py
@@ -1,9 +1,13 @@
 import torch
 
-# Necessary map for it to work with simple sampler, do not include steps in the settings as it gets added automatically.
+# Define the settings for the sigmoid function scheduler
+# Note: Do not include 'steps' in the settings as it gets added automatically.
+# The settings dictionary should have the same names as the parameters in the get_sigmas function.
 settings = {
     "name": "sigmoid",
-    "settings": { # name: [type, default value, min val, max val, snap to, round] Note: this currently only supports floats. 
+    "settings": {
+        # Format: "parameter_name": [type, default_value, min_value, max_value, step_value, round_flag]
+        # Types supported: FLOAT, INT, STRING, BOOLEAN
         "sigma_max_sig": ["FLOAT", 25.0, 0.0, 5000.0, 0.01, False],
         "sigma_min_sig": ["FLOAT", 0.0, 0.0, 5000.0, 0.01, False],
         "steepness": ["FLOAT", 3.5, 0.0, 10.0, 0.01, False],
@@ -11,7 +15,8 @@ settings = {
     }
 }
 
-# A scheduler must have a function called "get_sigmas" to work properly, its first input must be the steps for it to work properly.
+# A scheduler must have a function called "get_sigmas" to work properly.
+# The first input must be the steps for it to work properly as the steps setting is automatically added.
 def get_sigmas(n, sigma_max_sig, sigma_min_sig, steepness=10, midpoint_ratio=0.5, device='cpu'):
     """
     Generates 'n' sigmas on an S-curve from sigma_max to sigma_min, with a controllable midpoint.
diff --git a/src/dynamic_scheduler_loader.py b/src/dynamic_scheduler_loader.py
index a2bd605..ed17ce9 100644
--- a/src/dynamic_scheduler_loader.py
+++ b/src/dynamic_scheduler_loader.py
@@ -2,13 +2,27 @@ from .custom_schedulers.custom_schedulers import CustomSchedulers
 
 def generate_scheduler_node_class(settings, get_sigmas_function):
     class DynamicSchedulerNode:
+
+        @classmethod
+        def create_setting_entry(setting_type, setting_value):
+            if setting_type == "INT":
+                return ("INT", {"default": setting_value[1], "min": setting_value[2], "max": setting_value[3]})
+            elif setting_type == "FLOAT":
+                return ("FLOAT", {"default": setting_value[1], "min": setting_value[2], "max": setting_value[3], "step": setting_value[4]})
+            elif setting_type == "STRING":
+                return ("STRING", {"default": setting_value[1]})
+            elif setting_type == "BOOLEAN":
+                return ("BOOLEAN", {"default": setting_value[1]})
+            else:
+                raise ValueError(f"Unsupported setting type: {setting_type}")
+
         @classmethod
         def INPUT_TYPES(cls):
             inputs = {
                 "required": {
                     "steps": ("INT", {"default": 20, "min": 1, "max": 10000}),
                     **{
-                        key: ("FLOAT", {"default": value[1], "min": value[2], "max": value[3], "step": value[4]})
+                        key: cls.create_setting_entry(value[0], value)
                         for key, value in settings['settings'].items()
                     }
                 }