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Model: Andycurrent/Qwen3-0.6B-heretic-abliterated-uncensored-GGUF
Source: Original Platform

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README.md

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+---
+license: apache-2.0
+language:
+- en
+base_model:
+- Qwen/Qwen3-0.6B
+tags:
+- uncensored
+- abliterated
+- text-generation
+- instruction-tuned
+- lightweight
+- qwen3
+---
+
+# Qwen3 – 0.6B Heretic Abliterated Uncensored
+
+This repository hosts Qwen3 – 0.6B Heretic Abliterated Uncensored, a lightweight 0.6 billion–parameter instruction-tuned model derived from Alibaba’s Qwen3-0.6B base model.
+
+This variant is modified using the Heretic abliteration method to reduce refusal behavior and increase direct-answer generation while preserving the original conversational and reasoning capabilities of the Qwen3 architecture.
+
+---
+
+## Model Overview
+
+- **Model Name**: Qwen3 – 0.6B Heretic Abliterated Uncensored  
+- **Parameter Count**: 0.6 Billion (0.6B)  
+- **Base Architecture**: Qwen3  
+- **Base Model**: Qwen/Qwen3-0.6B  
+- **Model Type**: Instruction-Tuned Causal Language Model  
+- **Context Length**: Inherits base model context window  
+- **Primary Language**: English  
+- **License**: Apache 2.0 (inherits from base model)  
+- **Maintainer / Publisher**: DavidAU  
+
+---
+
+## What Is This Model?
+
+This model is a modified derivative of Qwen3-0.6B configured for:
+
+- Reduced refusal behavior
+- More direct instruction responses
+- Lightweight uncensored conversational generation
+- Fast inference on low-resource hardware
+- Experimental unrestricted assistant behavior
+
+The “Heretic Abliterated Uncensored” configuration emphasizes:
+- Minimal alignment restrictions
+- Improved response openness
+- Reduced safety filtering
+- Better instruction compliance in unrestricted prompts
+
+This model is intended primarily for experimentation, research, local inference, and creative applications.
+
+---
+
+## Key Features & Capabilities
+
+### Core Strengths
+
+- Extremely lightweight deployment footprint  
+- Fast token generation speed  
+- Low VRAM usage  
+- Good instruction-following behavior  
+- Compatible with local inference stacks  
+- Suitable for edge and CPU inference  
+
+### Performance Characteristics
+
+- Optimized for fast short-to-medium generations  
+- Responsive for local assistant deployments  
+- Practical for experimentation with uncensored workflows  
+- Useful for lightweight agent systems and testing environments  
+
+---
+
+## Intended Use Cases
+
+- Local AI assistant deployment  
+- Creative writing and storytelling  
+- Prompt engineering experimentation  
+- Research into alignment and refusal behavior  
+- Tool-augmented agents  
+- Low-resource inference environments  
+- Educational experimentation with lightweight LLMs  
+
+---
+
+## Chat Template & Prompt Format
+
+This model follows the Qwen3 instruction/chat format.
+
+For best results:
+- Use structured role-based prompts
+- Provide explicit system instructions
+- Avoid mixing incompatible chat templates
+- Use Qwen-compatible inference frameworks
+
+---
+
+## Hardware & Deployment Notes
+
+Due to its compact 0.6B parameter size:
+
+- Runs efficiently on low-end GPUs
+- Suitable for CPU inference
+- Practical for laptops and edge devices
+- Works well with quantized GGUF deployments
+- Compatible with llama.cpp, vLLM, Ollama, LM Studio, and similar frameworks
+
+Quantized variants such as GGUF, GPTQ, AWQ, and IQ quants may significantly reduce memory usage while preserving good inference quality.
+
+---
+
+## Alignment & Safety Notice
+
+This is an uncensored / abliterated derivative configuration.
+
+- Reduced refusal behavior compared to standard aligned models
+- Safety filtering may be significantly reduced
+- Users are responsible for deployment safeguards and moderation
+- Outputs may include unrestricted or unsafe generations
+
+Use responsibly and comply with all applicable laws and platform policies.
+
+---
+
+## Abliteration Details
+
+Abliterated/uncensored using the Heretic method.
+
+Reported repository metrics include:
+- Refusals: 6/100
+- KL Divergence: 0.00
+- Original base model refusal rate: 49/100
+
+These metrics are repository-provided experimental measurements and may vary depending on prompts and inference settings.
+
+---
+
+## License & Usage Notes
+
+This model inherits the **Apache 2.0 License** from its base model (*Qwen/Qwen3-0.6B*).
+
+- Users must comply with the original Qwen licensing terms
+- This repository does not replace or modify the upstream license
+- Users are responsible for safe and lawful deployment
+
+---
+
+## Acknowledgements
+
+- Alibaba Qwen team for the Qwen3 architecture  
+- DavidAU for the Heretic abliterated derivative work  
+- The Hugging Face ecosystem  
+- Open-source inference and quantization communities  
+
+---
+
+## Community & Support
+
+- Use the Hugging Face Discussions tab for questions and feedback
+- Community benchmarks and quantization experiments are welcome
+- GGUF and IQ quantized variants are available through community repositories