diff --git a/README.md b/README.md
index 3b3824714..bfa8904df 100644
--- a/README.md
+++ b/README.md
@@ -56,6 +56,7 @@ Workflow examples can be found on the [Examples page](https://comfyanonymous.git
 | Q | Toggle visibility of the queue |
 | H | Toggle visibility of history |
 | R | Refresh graph |
+| Double-Click LMB | Open node quick search palette |
 
 Ctrl can also be replaced with Cmd instead for MacOS users
 
diff --git a/comfy/model_management.py b/comfy/model_management.py
index 7070912df..39df8d9a7 100644
--- a/comfy/model_management.py
+++ b/comfy/model_management.py
@@ -275,8 +275,17 @@ def xformers_enabled_vae():
     return XFORMERS_ENABLED_VAE
 
 def pytorch_attention_enabled():
+    global ENABLE_PYTORCH_ATTENTION
     return ENABLE_PYTORCH_ATTENTION
 
+def pytorch_attention_flash_attention():
+    global ENABLE_PYTORCH_ATTENTION
+    if ENABLE_PYTORCH_ATTENTION:
+        #TODO: more reliable way of checking for flash attention?
+        if torch.version.cuda: #pytorch flash attention only works on Nvidia
+            return True
+    return False
+
 def get_free_memory(dev=None, torch_free_too=False):
     global xpu_available
     global directml_enabled
@@ -312,7 +321,12 @@ def maximum_batch_area():
         return 0
 
     memory_free = get_free_memory() / (1024 * 1024)
-    area = ((memory_free - 1024) * 0.9) / (0.6)
+    if xformers_enabled() or pytorch_attention_flash_attention():
+        #TODO: this needs to be tweaked
+        area = 20 * memory_free
+    else:
+        #TODO: this formula is because AMD sucks and has memory management issues which might be fixed in the future
+        area = ((memory_free - 1024) * 0.9) / (0.6)
     return int(max(area, 0))
 
 def cpu_mode():
diff --git a/nodes.py b/nodes.py
index bc1d34c43..20776bb37 100644
--- a/nodes.py
+++ b/nodes.py
@@ -105,15 +105,13 @@ class ConditioningSetArea:
 
     CATEGORY = "conditioning"
 
-    def append(self, conditioning, width, height, x, y, strength, min_sigma=0.0, max_sigma=99.0):
+    def append(self, conditioning, width, height, x, y, strength):
         c = []
         for t in conditioning:
             n = [t[0], t[1].copy()]
             n[1]['area'] = (height // 8, width // 8, y // 8, x // 8)
             n[1]['strength'] = strength
             n[1]['set_area_to_bounds'] = False
-            n[1]['min_sigma'] = min_sigma
-            n[1]['max_sigma'] = max_sigma
             c.append(n)
         return (c, )