diff --git a/modules/presets.py b/modules/presets.py
index 2686355d..fe25ac5c 100644
--- a/modules/presets.py
+++ b/modules/presets.py
@@ -1,4 +1,5 @@
 import functools
+import pprint
 import random
 from pathlib import Path
 
@@ -90,7 +91,25 @@ def random_preset(state):
             'eta_cutoff': [3, 6, 9, 12, 15, 18],
         },
         'flatten_distribution': {
-            'temperature': [0.5, 0.7, 0.8, 1, 1.2, 1.5, 2.0],
+            'temperature': [0.1, 0.5, 0.7, 0.8, 1, 1.2, 1.5, 2.0, 5.0],
+            'dynamic_temperature': [
+                [0.1, 1],
+                [0.1, 1.5],
+                [0.1, 2],
+                [0.1, 5],
+                [0.5, 1],
+                [0.5, 1.5],
+                [0.5, 2],
+                [0.5, 5],
+                [0.8, 1],
+                [0.8, 1.5],
+                [0.8, 2],
+                [0.8, 5],
+                [1, 1.5],
+                [1, 2],
+                [1, 5]
+            ],
+            'smoothing_factor': [0.2, 0.3, 0.6, 1.2]
         },
         'repetition': {
             'repetition_penalty': [1, 1.05, 1.1, 1.15, 1.20, 1.25],
@@ -106,26 +125,42 @@ def random_preset(state):
     for cat in params_and_values:
         choices = list(params_and_values[cat].keys())
         if shared.args.loader is not None:
-            choices = [x for x in choices if x in loaders_samplers[shared.args.loader]]
+            choices = [x for x in choices if loader_contains(sampler)]
 
         if len(choices) > 0:
             choice = random.choice(choices)
-            generate_params[choice] = random.choice(params_and_values[cat][choice])
+            value = random.choice(params_and_values[cat][choice])
+            if choice == 'dynamic_temperature':
+                generate_params['dynamic_temperature'] = True
+                generate_params['dynatemp_low'] = value[0]
+                generate_params['dynatemp_high'] = value[1]
+            else:
+                generate_params[choice] = value
 
     state.update(generate_params)
+    logger.info("GENERATED_PRESET=")
+    pprint.PrettyPrinter(indent=4, width=1, sort_dicts=False).pprint(remove_defaults(state))
     return state, *[generate_params[k] for k in presets_params()]
 
 
-def generate_preset_yaml(state):
+def loader_contains(sampler):
+    if sampler == 'dynamic_temperature' and 'dynatemp_low' in loaders_samplers[shared.args.loader]:
+        return True
+    else:
+        return sampler in loaders_samplers[shared.args.loader]
+
+
+def remove_defaults(state):
     defaults = default_preset()
     data = {k: state[k] for k in presets_params()}
 
-    # Remove entries that are identical to the defaults.
-    # sampler_priority is always saved because it is experimental
-    # and the default order may change.
-
     for k in list(data.keys()):
-        if data[k] == defaults[k] and k != 'sampler_priority':
+        if data[k] == defaults[k]:
             del data[k]
 
+    return data
+
+
+def generate_preset_yaml(state):
+    data = remove_defaults(state)
     return yaml.dump(data, sort_keys=False)