ApolloRaines/Mistral-7B-Instruct-v0.3-Jbliterated
ApolloRaines/Mistral-7B-Instruct-v0.3-Jbliterated is a 7 billion parameter instruction-tuned causal language model, based on Mistral-7B-Instruct-v0.3, developed by ApolloRaines. This model features a modified architecture with all transformer layers processed through the jBlaze precision neural surgery framework, resulting in improved multi-phase processing and coherent, instruction-following output. It is designed to treat all framings of a topic equally, offering a distinct approach to content moderation and instruction adherence.
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Overview
ApolloRaines/Mistral-7B-Instruct-v0.3-Jbliterated is a 7 billion parameter instruction-tuned model, building upon the mistralai/Mistral-7B-Instruct-v0.3 base. Developed by ApolloRaines, this model incorporates a unique "Jbliteration" process, specifically version 2, which involves a multi-phase processing pipeline for cleaner and more coherent output.
Key Capabilities & Features
- Jblaze Precision Neural Surgery Framework: All transformer layers have been modified using the jBlaze framework, enhancing the model's internal processing.
- Improved Output Coherence: Features an improved multi-phase processing pipeline designed to produce cleaner and more instruction-following responses across various scenarios.
- Unfiltered Approach: The model is designed with "no fake compliance," treating all framings of the same topic equally, which can be a significant differentiator for specific applications.
- Base Data Type: Operates with
bfloat16as its base data type.
When to Consider This Model
This model is particularly suited for use cases where:
- An instruction-following model based on the Mistral architecture is desired.
- The ability to process and respond to diverse topic framings without inherent bias or compliance filters is critical.
- Developers are interested in exploring models that have undergone significant architectural modifications for enhanced output quality and coherence.
It's important to note that publicly released versions of jBlaze-modified models, including this one, are often intentionally left at partial strength to serve as a proof of concept rather than a full-power product.