Yingyaeliae/Ariel-Alloy-V1-24B-Extra-Heretic-Sauce
Yingyaeliae/Ariel-Alloy-V1-24B-Extra-Heretic-Sauce is a 24 billion parameter language model, derived from ShyliaSafetensors/Ariel-Alloy-V1-24B-Heretic and further processed using Heretic v1.4.0. This model is specifically optimized for role-play scenarios by significantly reducing refusal rates, achieving 2 refusals per 100 prompts compared to 9 refusals in its direct predecessor. It was created through a multi-step merging process involving SLERP, Dare-Ties, and Model Stock methods, integrating several specialized base models to enhance its conversational and creative capabilities.
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Overview
Yingyaeliae/Ariel-Alloy-V1-24B-Extra-Heretic-Sauce is a 24 billion parameter language model, building upon the foundation of ShyliaSafetensors/Ariel-Alloy-V1-24B-Heretic. Its primary distinction lies in its enhanced "decensored" nature, achieved through further processing with Heretic v1.4.0. This iteration focuses on minimizing model refusals, making it more suitable for open-ended and creative interactions.
Key Capabilities
- Reduced Refusal Rate: Demonstrates a significantly lower refusal rate of 2/100, compared to 9/100 in its direct predecessor and 98/100 before Heretic processing, indicating a more permissive and less restrictive output.
- Role-Play Optimization: The model's development goal was to create a stable and effective model for role-playing, achieved through a complex multi-step merging strategy.
- Advanced Merging Techniques: Constructed using a combination of SLERP, Dare-Ties, and Model Stock merge methods, integrating various specialized base models like Magidonia-24B-v4.3-heretic and Dans-PersonalityEngine-V1.3.0-24b.
Good For
- Creative Role-Playing: Ideal for applications requiring a highly unconstrained and responsive model for character interactions and narrative generation.
- Uncensored Content Generation: Suitable for use cases where strict content filtering is undesirable, offering greater freedom in responses.
- Experimental AI Development: Useful for researchers and developers exploring the boundaries of language model behavior and control over refusal mechanisms.