<h1 id="femix_hassakuxl-lqgk6izfq">Femix_HassakuXL</h1>FeMix_HassakuXL is a series of Stable Diffusion XL models designed for generating anime-style images, employing a unique blend strategy to combine different aesthetic styles. The series ranges from highly stylized and experimental blends to stable, high-quality models suitable for general use. FeMix_HassakuXL merges two distinct models and concepts of each blend, to achieve various output depending on users needs.<h2 id="recommended-prompts-and-settings-6wunwy92d">Recommended Prompts &amp; Settings</h2><ol><li>Quality Prompts: <code>masterpiece, best quality, detailed</code></li><li>Negative Prompts: <code>worst quality, bad quality, sketch</code>. Adding "signature" can help remove unintended watermarks.</li><li>High-Quality faces: Put <code>nose</code> into the negative prompt for smooth faces, if you feel that Style A gets too prominent.</li><li>Sampling Method: DPM++ 2M Karras. Some users experience good results with Euler A and different samplers due to having weaker style implementation to improve image creation.</li><li>General Settings: Resolution 832x1216. Try varying different resolutions for unique image output.</li></ol><h2 id="general-recommendations:-x36wulgfl">General Recommendations:</h2>Avoid overloading the model with lengthy prompts. Its versatility is also its weakness, as too much information can lead to unpredictable results.Excluded metadata and franchise tags, so please do not use them.<h2 id="negative-recommendations:-s12f7dv17">Negative Recommendations:</h2>* Avoid using disruptive features: floating texts, logos, watermarks, speak bubbles, signatures. If those results occur, add "signature" into the negative prompt.* Excluded metadata and franchise tags, do not use them.<h2 id="recommended-resolutions-(sdxl):-8wtrkrga3">Recommended Resolutions (SDXL):</h2>* 1024 x 1024* 1152 x 896* 896 x 1152* 1216 x 832* 832 x 1216 (most recommended)* 1344 x 768* 768 x 1344* 1536 x 640* 640 x 1536<h2 id="license-info:-nqc2gw31h">License Info:</h2>This model merges aspects from ANIMAGINE XL 3.0 (pre-V1) and Illustrious-XL &amp; WAI-NSFW-illustrious-SDXL (V1 onwards):Fair AI Public License 1.0-SD.

FeMix_HassakuXL

<ul><li>Base Blend: Built on the Style A9B1 (90% Style A, 10% Style B) FeMix blend strategy. This blend continues to strongly favor Style A, introducing an extremely subtle touch of Style B.</li><li>HassakuXL v2.1 CLIP Integration: Leverages the enhanced CLIP (Contrastive Language-Image Pre-training) from HassakuXL v2.1. Expect to see increased accuracy in translating text prompts into relevant image features, while retaining the core characteristics of Style A.</li><li>HassakuXL v2.1 VAE Integration: Includes the improved VAE (Variational Autoencoder) from HassakuXL v2.1. Aims to enhance image clarity, sharpen details, and minimize artifacts, resulting in a more polished visual outcome. The subtle effect from Style B may also become better and easier to notice.</li><li>Incredibly Subtle Style B Influence: The 10% influence from Style B remains extremely subtle. Look for slight variances in color grading, subtle shifts in texture, and a minor stylistic touch.</li><li>Minimal Artifact Risk: Due to the dominance of Style A, the risk of generating noticeable artifacts is almost nonexistent.</li><li>Excellent LoRA Compatibility: LoRA models should perform predictably and effectively. Expect to harness LoRAs without facing the unexpected challenges of an experimental model.</li><li>Traditional Prompts Recommended: This model is designed to be easy to use. Utilize common prompts without encountering unpredictable results.</li><li>An Ideal Blend: By implementing Style B in an extremely subtle way, the enhanced results is something that can be enjoyed by many.</li><li>Highres Fix/Adetailer Largely Optional: Expect impressive results to a point where post-processing is down to a personal preference.</li></ul>In summary: With Style A heavily emphasized, this blend gives a high-quality product with minor StyleB. With Style A being the star of this blend, you can expect a stable and high-quality output while having a unique image, and makes this model a base standard to be used for general use.

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