Update README.md

README.md

@@ -5,9 +5,9 @@ tags:
 - nsfw
 - merge
 ---
-<span style="color:orange">I'm just tinkering. All credit to the original creators: [Noromaid is hot.](https://huggingface.co/NeverSleep)</br>
-"rpcal" designates that this model was quantized using an [RP-specific data set](https://huggingface.co/datasets/royallab/PIPPA-cleaned) instead of the generalized wiki or llama data set. I have been unable to quantify real differences in the same model "compressed" using these two different methods. It "feels" better, but I can't put my finger on why. My current theory is that it gives "good responses" just as often as a similarly quantized model, however, good responses are "subjectively better" with this method. Any help quantifying this would be appreciated. [Anyone know Ayumi?](https://ayumi.m8geil.de/erp4_chatlogs/?S=erv3_0#!/index)</br>
-This model: EXL2 @ 3.5 bpw using RP data for calibration.</br></span>
+<span style="color:orange"><ul><li>I'm just tinkering. All credit to the original creators: [Noromaid is hot.](https://huggingface.co/NeverSleep)</li>
+"rpcal" designates that this model was quantized using an [RP-specific data set](https://huggingface.co/datasets/royallab/PIPPA-cleaned) instead of the generalized wiki or llama data set. I have been unable to quantify real differences in the same model "compressed" using these two different methods. It "feels" better, but I can't put my finger on why. My current theory is that it gives "good responses" just as often as a similarly quantized model, however, good responses are "subjectively better" with this method. Any help quantifying this would be appreciated. [Anyone know Ayumi?](https://ayumi.m8geil.de/erp4_chatlogs/?S=erv3_0#!/index)</li>
+This model: EXL2 @ 3.5 bpw using RP data for calibration.</li></ul></span>
 
 ## MiquMaid v3