The quantized model files are available for download. Click the buttons below to view the files.

For the best roleplaying experience, it is highly recommended to use the provided character card and lore book. These files help guide the model's persona and provide rich, in-universe context.

For a seamless setup in SillyTavern, you can download pre-configured sampler presets. These are tuned to provide an optimal balance between creativity and narrative coherence for this model.

Simply download the .json file below and import it into SillyTavern's sampler presets menu.

For the best results, use this structured format. This helps the AI clearly distinguish between actions, inner thoughts, and dialogue.

Standard novel-style formatting is also understood, but this structured format is preferred for clarity.

This is Version 12, a significant advancement in the Animus series built on a completely new training philosophy. Instead of merging previous models, V12 is a direct fine-tune of Llama 3.3 70B Instruct. This focused approach has resulted in what is being called the most coherent and lore-adherent version to date.

V12's strength comes from a novel dataset designed to teach the model the why behind the lore, not just the what. The training data is a mix of:

The result is a model with exceptionally strong prose and a deep grasp of in-universe lore, making for a highly immersive and accurate roleplaying experience.

V12 marks a shift from model merging to a focused, direct fine-tuning approach. This allows for greater control over the final model's characteristics.

A key feature in previous test versions—the presentation of multiple-choice actions (e.g., A, B, C) to guide the user—has been removed.

While a promising concept, this feature needs further refinement to ensure it enhances, rather than restricts, the roleplaying experience. It may be reintroduced in a more polished form in a future release. For now, the model returns to a more traditional, open-ended prose format.

The V12 dataset consists of 6,000 high-quality examples, a combination of two distinct types:

Both datasets underwent a rigorous cleaning process to remove formatting artifacts, such as **scene transitions**, resulting in a cleaner and more natural narrative style.