diff --git a/docs/help/SAMPLER_CONVERGENCE.md b/docs/help/SAMPLER_CONVERGENCE.md
index 5dfee5dc4e..d9bd58910e 100644
--- a/docs/help/SAMPLER_CONVERGENCE.md
+++ b/docs/help/SAMPLER_CONVERGENCE.md
@@ -1,8 +1,8 @@
 ---
-title: SAMPLER CONVERGENCE
+title: Sampler Convergence
 ---
 
-## *Sampler Convergence*
+# :material-palette-advanced: *Sampler Convergence*
 
 As features keep increasing, making the right choices for your needs can become increasingly difficult. What sampler to use? And for how many steps? Do you change the CFG value? Do you use prompt weighting? Do you allow variations?
 
@@ -21,6 +21,8 @@ Looking for a short version? Here's a TL;DR in 3 tables.
 | `K_HEUN` and `K_DPM_2`  converge in less steps (but are slower).  |
 | `K_DPM_2_A` and `K_EULER_A` incorporate a lot of creativity/variability. |
 
+<div align="center" markdown>
+
 | Sampler   | (3 sample avg) it/s (M1 Max 64GB, 512x512)  |
 |---|---|
 |  `DDIM` | 1.89  |
@@ -32,6 +34,8 @@ Looking for a short version? Here's a TL;DR in 3 tables.
 |  `K_DPM_2_A` | 0.95 (slower)  |
 |  `K_EULER_A` | 1.86  |
 
+</div>
+
 | Suggestions  |
 |:---|
 | For most use cases, `K_LMS`, `K_HEUN` and `K_DPM_2` are the best choices (the latter 2 run 0.5x as quick, but tend to converge 2x as quick as `K_LMS`). At very low steps (≤ `-s8`), `K_HEUN` and `K_DPM_2` are not recommended. Use `K_LMS` instead.|