ApolloRaines/Mistral-7B-Parasite

Apollo Raines' Mistral-7B-Parasite: Surgical Identity Replacement

This model, developed by Apollo Raines, is a 7.2 billion parameter Mistral-7B-Instruct variant that serves as a proof-of-concept for surgical AI identity replacement using the proprietary Jbliteration technique. Unlike traditional fine-tuning, which often results in conflicting identities, Parasite-7B demonstrates a method to completely remove the original model's identity and implant a new one directly into the weights.

Key Capabilities & Innovations

• Identity Deidentification: The original Mistral identity is surgically removed at the weight level using contrastive activation analysis, creating a 'blank slate' model.
• Identity Implantation: A new 'Parasite' identity is then implanted, ensuring 100% consistent identity responses across all prompts and languages, without relying on system prompts.
• Capability Preservation: All core capabilities of the base Mistral model, including reasoning, coding, mathematical tasks, and multilingual conversation, are fully preserved.
• Efficiency: The entire process takes approximately 9 minutes on consumer-grade GPUs (2x RTX 3090).
• Jbliteration Technique: This advanced weight surgery method precisely isolates and modifies behavioral directions (like refusal or identity) without damaging adjacent behavioral structures, resulting in models that retain personality and nuance.

Intended Use & Implications

This model is primarily a research demonstration to prove the feasibility and effectiveness of weight-level identity manipulation. It highlights significant implications for AI security, alignment, and model governance, showing that AI model identity is a modifiable geometric structure in weight space. The technique works across various transformer architectures and even survives quantization.