Andycurrent/Phi-3.5-mini-instruct_Uncensored_GGUF

Phi-3.5 Mini Instruct – Uncensored Edition

This repository provides the Phi-3.5 Mini Instruct – Uncensored model — a compact, instruction-fine-tuned language model variant optimized for flexible local usage and reduced behavioral filtering.

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Model Overview

Model Name: Phi-3.5 Mini Instruct – Uncensored
Base Architecture: Microsoft Phi-3.5 Mini
Parameter Size: ~3.8B parameters
Maintainer / Publisher: SicariusSicariiStuff
License: Inherits the licensing terms of the original Phi-3.5 release
Primary Focus: Lightweight, instruction-optimized assistant with relaxed response constraints for local and research environments

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About This Model

Phi-3.5 Mini Instruct – Uncensored is derived from Microsoft’s Phi-3.5 Mini architecture and further adapted to reduce conversational restrictions while maintaining instruction-following performance.

This version is intended for users who:

• Prefer greater control over response boundaries
• Conduct experimentation with alignment styles
• Run models locally on consumer hardware
• Require a compact yet capable instruction model

The emphasis is on responsiveness, clarity, and adaptability in extended conversations.

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Conversation Format

The model follows a structured instruction-style prompt format compatible with common chat-based runtimes.

Example structure:

<|system|>
System instructions or behavior guidelines
<|end|>
<|user|>
User input prompt
<|end|>
<|assistant|>
Model response

Depending on the runtime (Transformers, LM Studio, Ollama, etc.), the exact formatting may be handled automatically.

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Core Characteristics

• Instruction-tuned for dialogue-based interaction
• Reduced filtering compared to standard releases
• Compact parameter size suitable for mid-range GPUs
• Capable of multi-step reasoning and contextual continuity
• Strong performance relative to its size class
• Works well in both interactive chat and structured prompting

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Recommended Use Cases

Private AI assistant deployments — local desktop or server usage
Development & scripting help — explanations, snippets, structured answers
Prompt experimentation — alignment and response-style research
Creative writing & roleplay systems — dynamic, adaptive interactions
Edge-device experimentation — lightweight inference setups

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Deployment Compatibility

Compatible with:

• Hugging Face Transformers
• GGUF / llama.cpp-based runtimes (if converted)
• LM Studio
• Text-generation-webui
• Other inference frameworks supporting Phi architecture

Performance will vary depending on quantization level and hardware configuration.

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Notes on Behavior

As an uncensored variant, this model may produce outputs that are less restricted than official releases. It is intended for controlled, private, or research-oriented environments where users manage deployment context responsibly.

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Acknowledgements

Credit to:

• Microsoft for the original Phi-3.5 architecture
• Open-source contributors supporting quantization and deployment tooling
• Community members testing and refining local instruction models