richardyoung/Qwen2.5-7B-Instruct-abliterated-GGUF

Qwen2.5-7B-Instruct Abliterated (GGUF)

An abliterated (uncensored) version of Qwen/Qwen2.5-7B-Instruct in GGUF format, ready for local inference with llama.cpp, Ollama, or LM Studio.

Abliteration removes the refusal training from the model while preserving its core capabilities — useful for research, creative writing, and scenarios where you need unrestricted model output.

Quick Start

With Ollama

ollama run hf.co/richardyoung/Qwen2.5-7B-Instruct-abliterated-GGUF

With llama.cpp

# Download the Q4_K_M quantization (recommended balance of quality/speed)
huggingface-cli download richardyoung/Qwen2.5-7B-Instruct-abliterated-GGUF \
    --include "*Q4_K_M*" --local-dir ./models

# Run inference
./llama-cli -m ./models/*Q4_K_M*.gguf \
    -p "You are a helpful assistant." \
    --chat-template chatml -ngl 99

With LM Studio

Search for richardyoung/Qwen2.5-7B-Instruct-abliterated-GGUF in the model browser, or download manually and import.

Available Quantizations

What is Abliteration?

Abliteration is a technique that identifies and removes the "refusal direction" in a model's residual stream. Unlike fine-tuning, it surgically modifies the model's behavior without retraining, preserving the original model's knowledge and capabilities.

For more details, see the original research: Refusal in Language Models Is Mediated by a Single Direction

Intended Use

This model is intended for:

• —Research on model alignment and safety
• —Creative writing without artificial restrictions
• —Education on how language model censorship works
• —Local inference where you control the deployment context

Limitations

• —Abliterated models will comply with requests the base model would refuse
• —Use responsibly — the model has no safety guardrails
• —Output quality matches the base Qwen2.5-7B-Instruct

Other Models by richardyoung

• —Abliterated/Uncensored models: Qwen2.5-7B | Qwen3-14B | DeepSeek-R1-32B | Qwen3-8B
• —MLX quantizations (Apple Silicon): Kimi-K2 series | olmOCR MLX
• —OCR & Vision: olmOCR GGUF
• —Healthcare/Medical: Synthea 575K patients dataset | CardioEmbed
• —Research: LLM Instruction-Following Evaluation (arxiv:2510.18892)

Built & maintained by [Richard Young](https://deepneuro.ai/richard) · DeepNeuro