This model is designed for high-fidelity, photorealistic human avatars, focusing on natural skin texture, facial structure, hair realism, and body proportions.
It is intended for cinematic scenes, storytelling, fashion, lifestyle, portraits, and realistic character creation.
The model was trained with clothed images. Any nudity or sexualized output may only occur when combined with external LoRAs or third-party tools, which are not part of this model.
Best results are achieved when used for realism, narrative scenes, and professional visual projects.
This model was developed over an extended period, with the goal of transforming artificial human avatars into highly realistic, consistent characters.
Training was performed across multiple platforms and workflows, including manual, hand-curated processes, to preserve facial identity, proportions, and realism over different scenes and generations.
One of the key strengths of this model is identity consistency — it does not easily lose facial structure or character coherence across outputs.
This version also includes testing using Civitai’s own Z-Turbo / experimental training pipeline, which is clearly marked by the platform as experimental and not fully guaranteed, as it is still under evaluation and refinement.
This model should be understood as a realism-focused experimental release, not a final or static product.
Description
Use of Partial , Human Body Representation, and Everyday Contexts
The models and LoRAs provided in this collection are designed for realistic human, bodily, and behavioral representation, depicting natural, everyday situations such as light clothing, sportswear, swimwear (bikinis, swim trunks, shorts), as well as domestic, urban, and leisure environments commonly observed across different cultures — particularly in tropical and coastal countries.
The occasional presence of shirtless torsos, tight-fitting clothing, bikinis, or partial body exposure does not constitute or . These elements represent socially accepted and real-world scenarios, including beaches, gyms, homes, sports activities, and non-sexualized moments of intimacy commonly found in daily life.
Regarding and
This project does not promote, encourage, or distribute .
All models were originally trained with clothed subjects, following ethical and technical standards for responsible AI development.
Any generation of , acts, or adult content is not inherent to the models provided here and can only occur through the intentional combination with external LoRAs, third-party tools, or additional services, which fall outside the scope and responsibility of this project.
Therefore, any inappropriate or output results solely from user-driven post-composition choices, and users are fully responsible for complying with local laws, platform policies, and ethical guidelines.
Training, Authorship, and Technical Responsibility
The models were developed and trained by an AI specialist focused on realistic avatar generation, who holds a global patent related to advanced multimodal realism and human representation techniques in artificial intelligence.
The training process followed strict technical criteria, including:
anatomical accuracy,
realistic texture and lighting,
natural posture and expression,
preservation of non-sexualized contextual integrity.
The primary purpose of these models is artistic, cinematic, advertising, educational, and experimental, including avatar creation, narrative scenes, visual simulations, and human-AI interaction studies.
User Responsibility
By using these models, the user acknowledges that:
• combining them with other LoRAs or services may significantly alter the final output;
• they are solely responsible for the appropriate and lawful use of generated content;
• they must comply with applicable local laws and platform policies.
The creators of these models assume no responsibility for misuse, illegal applications, or content generated beyond the originally intended scope.
Details
Files
Available On (1 platform)
Same model published on other platforms. May have additional downloads or version variants.