Update README.md

README.md

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 - nsfw
 - merge
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-*<span style="color:orange">I'm just tinkering. All credit to the original creators: [Noromaid is hot.](https://huggingface.co/NeverSleep)</span>
-*<span style="color:orange">"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)</span>
-*<span style="color:orange">This model: EXL2 @ 3.5 bpw using RP data for calibration.</span>
+* <span style="color:orange">I'm just tinkering. All credit to the original creators: [Noromaid is hot.](https://huggingface.co/NeverSleep)</span>
+* <span style="color:orange">"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)</span>
+* <span style="color:orange">This model: EXL2 @ 3.5 bpw using RP data for calibration.</span>
 
 ## MiquMaid v3