Update README.md

README.md

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         <h2>🎨 CardProjector v4 tricks</h2> <!-- Heading changed, emoji kept for style consistency -->
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         <ul>
-            <li>Due to its ability to think - CardThinker V3 32B works through characters much deeper, more thoroughly, and logically.</li>
-            <li>Because of the peculiarities of the base model QwQ, this model has VERY well-developed creative writing skills (to the extent that I found the most usable temperature range to be 0.1-0.3).</li>
-            <li>Among the major drawbacks - high positive bias; CardThinker V3 tries to create an ideal friendly character. Even if you write "be sure to come up with negative personality traits" (or something along those lines), it will come up with traits that are too soft and harmless. To create a negative character, you have to fully come up with such traits yourself and then make the model develop them. Because of all this, in my opinion, CardProjector 24B V3 produces more vivid negative characters.</li>
+            <li>Absolute focus on personality development! This version places an absolute emphasis on designing character personalities, focusing on depth and realism. Eight (!) large datasets were collected, oriented towards all aspects of in-depth personality development. Extensive training was also conducted on a dataset of MBTI profiles with Enneagrams from psychology. The model was carefully trained to select the correct personality type according to both the MBTI and Enneagram systems. I highly recommend using these systems (see Usage recommendations); they provide an incredible boost to character realism. I conducted numerous tests with many RP models ranging from 24-70B parameters, and the MBTI profile system significantly impacts the understanding of the character's personality (especially on 70B models), making the role-playing performance much more realistic. You can see an example of a character's MBTI profile here. Currently, version V4 yields the deepest and most realistic characters.</li>
+            <li>Reduced likelihood of positive bias! I collected a large toxic dataset focused on creating and editing aggressive, extremely cruel, and hypersexualized characters, as well as transforming already "good harmless" characters into extremely cruel anti-versions of the original. Thanks to this, it was possible to significantly reduce the overall positive bias (especially in Gemma 3, where it is quite pronounced in its vanilla state), and make the model more balanced and realistic in terms of creating negative characters. It will no longer strive at all costs to create a cute, kind, ideal character, unless specifically asked to do so.</li>
+            <li>Moving to Gemma 3! After a series of experiments, it turned out that this model is ideally suited for the task of character design, as it possesses much more developed creative writing skills and higher general knowledge compared to Mistral 2501 in its vanilla state. Gemma 3 also seemed much more logical than its French competitor.</li>
+            <li>Vision ability! Due to the reason mentioned in the point above, you can freely use vision in this version. If you are using GGUF, you can download the mmproj model for the 27B version from bartowski (a vanilla mmproj will suffice, as I didn't perform vision tuning).</li>
+            <li>The overall quality of character generation has been significantly increased by expanding the dataset approximately 5 times compared to version V3.</li>
         </ul>
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             <h3>💡 Usage Recommendations</h3> <!-- Heading from second card -->