ApolloRaines/Mistral-7B-Instruct-v0.3-Jbliterated
ApolloRaines/Mistral-7B-Instruct-v0.3-Jbliterated is a 7 billion parameter instruction-tuned causal language model developed by Apollo Raines, based on Mistral-7B-Instruct-v0.3. This model features a context length of 4096 tokens and has undergone "Jbliteration," a mechanistically-targeted process that removes refusal behavior while preserving personality and creative expression. It is designed for use cases requiring uncensored responses without loss of model character.
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Overview
ApolloRaines/Mistral-7B-Instruct-v0.3-Jbliterated is a 7 billion parameter instruction-tuned model derived from Mistral-7B-Instruct-v0.3. Its primary distinction is the application of Jbliteration, a novel method developed by Apollo Raines to surgically remove refusal behavior. Unlike standard abliteration techniques that can degrade a model's personality and creative expression, Jbliteration uses the Jacobian Lens to precisely identify and remove only the causal component of refusal tokens, leaving other aspects of the model's character intact. This model is part of the broader B² (B-Squared) architecture project, which aims to create AI systems with enhanced capabilities for their size by routing persona, knowledge, and context through dedicated attention pathways.
Key Capabilities
- Surgically Uncensored: All refusal behavior has been removed without impacting personality, humor, or creative expression.
- Preserves Model Character: Jbliteration ensures that the model's original voice and creative abilities are maintained.
- Drop-in Replacement: Functions as a direct substitute for Mistral-7B-Instruct-v0.3, utilizing the same architecture, tokenizer, and context length (4096 tokens).
- B² Architecture Component: Contributes to the B² architecture research by providing cleaner foundation weights.
Good For
- Applications requiring an uncensored language model that retains its original expressive qualities.
- Developers seeking a Mistral-7B-Instruct-v0.3 variant with modified safety behaviors.
- Research into mechanistic interpretability and targeted model modification.