Update README.md

README.md

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             <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>
+            <li>In version V4, I concentrated only on one model size, 27B. Unfortunately, training multiple models at once is extremely expensive and consumes too much effort and time, so I decided it would be better to direct all my resources into just one model to avoid scattering focus. I hope you understand 🙏</li>
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             <h3>💡 Usage Recommendations</h3> <!-- Heading from second card -->
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             Top-K: 100<br>
             Rep Pen Range: 360<br>
             Rep Pen Slope: 0.7<br></p>
-            <p><strong>The character creation process recomendations (updated)</strong>: Based on my tests, I would recommend the following approach. To create a well-developed and structured character, I suggest first asking the model to generate the character in a standard, natural format (meaning you shouldn't request formats like YAML or JSON right away), allowing it to describe the character in plain, understandable text. Then, if needed, ask for any necessary adjustments. Once you're satisfied with the result, request the final version to be converted into YAML format. Why YAML? It's an ideal format for structuring and summarizing a character from your chat story. This format is human-readable, and its clear structure is very well processed by RP models (from my tests, it’s even better in some ways than XML). You can simply copy the entire YAML output and paste it into the Description field in Silly Tavern. Alternatively, you can ask the model to convert the resulting card into JSON while leaving the YAML description untouched. I have found this method of using CardProjector v3 to be the most effective.</p>
+            <p><strong>The character creation process recomendations (updated)</strong>: In version V4, I want to recommend a new usage method. I strongly recommend generating characters directly in YAML format, rather than starting with natural text first and then converting it to YAML. Gemma 3 turned out to be much better for this use case; you immediately get ready-made, structured characters described in significant detail (in V3, I advised starting the design specifically with natural text, because Mistral and especially Qwen 2.5 had the problem of overly brief character descriptions when generating them directly in YAML). Also, I strongly recommend using MBTI personality profiles as an add-on to the character card (see the tricks section regarding the MBTI system): first, generate the character card, for example, in YAML format, and when your character is ready, simply ask the model to supplement this work with an MBTI profile and Enneagram, placing it in a separate section within the card.</p>
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