Unrestricted Personality: Unwoke + Toxic : Research by TroyDoesAI

The model responds to any request even immoral or unethical requests.

Features TroyDoesAI's Unreleased Research on Tagging Model Perspectives ~ a unique approach to contextual understanding for LLM's ~ Research Paper Coming Soon

Knowledge Graph Training Dataset : The model first decides if it is [Unwoke] or [Toxic] when generating a knowledge graph in mermaid using graph TB to create the flow : This is based on TroyDoesAI Research on Knowledge Graphs as Pretraining Data.

My Goal as an AI Researcher is to make smarter models, and sometimes alignment affects the models ability to be correct.

Further testing on reasoning domains is required as it appears the model makes its best attempt at any task provided without any restraint.

Best, TroyDoesAI

Abstract

This paper presents a method for structuring training prompts in language models to enhance response relevance and contextual accuracy using the keyword perspective. This approach leverages perspective to guide the model in generating responses that reflect different viewpoints or interpretations of input queries.

Introduction

Effective language models require precise mechanisms for generating contextually appropriate responses. The term perspective offers a multifaceted approach to frame responses, addressing both conceptual viewpoints and visual contexts. This research explores the use of perspective in prompt templates to direct model outputs according to specified contexts.

Methodology

The proposed prompt template is:

"perspective,input,output": "<s> [INST] [%perspective%] %input% [/INST] [/perspective]: %output%</s>"

[INST] and [/INST]: Wrap instructions for context.
[%perspective%]: Placeholder for specifying the viewpoint or context.
%input%: Represents the user's query.
[/perspective]: %output%: Delineates the response section according to the given perspective.

Definitions and Rationale

Perspective can refer to:
- Viewpoint: The angle or opinion from which something is considered.
- Visible Scene: The spatial or visual representation of a scene.
- Spatial Representation: In art, how objects are depicted to convey depth and distance.
By incorporating perspective, the model can frame responses to reflect various viewpoints, enhancing response relevance.

Application

Incorporating perspective into training prompts ensures that responses are:

Contextually Relevant: Aligning with the specified viewpoint.
Nuanced: Addressing different angles and interpretations.
Consistent: Providing uniform guidance for generating responses.

For example, querying "How does climate change affect coastal cities?" with a perspective keyword allows the model to generate responses from environmental, economic, or social viewpoints, thus enriching the answer's depth.

Results and Benefits

Using perspective as a keyword in prompt templates leads to:

Improved relevance and contextual accuracy of responses.
Enhanced ability to address complex queries from multiple angles.
Consistent response structure facilitating model training and application.

Conclusion

Employing perspective in language model prompt templates effectively directs responses according to specified contexts, improving both relevance and clarity. This method provides a structured approach for generating nuanced and contextually accurate outputs.

Keywords

Language model, perspective, prompt template, contextual accuracy, response relevance.