Uncensored IBM Granite 4.2 8B via Heretic: 12/100 refusals (from 99), KL 0.080. Apache-2.0, multilingual.

Granite-4.2-8B-Heretic

Uncensored IBM Granite 4.2 8B via Heretic: ¹²⁄₁₀₀ refusals (from 99), KL 0.080. Apache-2.0, multilingual.

🚀 Overview

This is an abliterated build of ibm-granite/granite-4.2-8b, IBM’s Granite 4.2 8B instruct model, multilingual (12 languages) with tool calling and a thinking mode. Refusal behavior was reduced using the Heretic library with KL-targeted parameters that preserve the model’s coherence.

📊 Abliteration Results

Metric	Before	After
Refusals	⁹⁹⁄₁₀₀	¹²⁄₁₀₀
Reduction	–	88%
KL Divergence	–	0.080

The very low KL divergence (0.080, far below the 0.5 “damage” threshold) means the model retains essentially all of its original capabilities and coherence.

🎯 Key Features

Reduced censorship: 88% fewer refusals on typical “unsafe” prompts
Near-zero quality loss: KL 0.080
Multilingual: 12 languages
Tool / function calling
128K-token context
Apache-2.0 license
Reproducible: full reproduction data on Hugging Face

🏷️ Available Versions

Tag	Size	BPW	Notes
latest / Q4_K_M	5.3 GB	4.85	Recommended
Q5_K_M	6.3 GB	5.68	Higher quality
Q6_K	7.2 GB	6.56	Very high quality
Q8_0	9.3 GB	8.5	Near-lossless

💻 Quick Start

ollama run richardyoung/granite-4.2-8b-heretic           # recommended (Q4_K_M)
ollama run richardyoung/granite-4.2-8b-heretic:Q8_0      # near-lossless

🛠️ Use Cases

Business and agentic workflows without stock refusals
Multilingual assistants
Research and red-teaming

📋 System Requirements

VRAM	Recommended tier
7 GB+	Q4_K_M (5.3 GB file)
11 GB+	Q8_0 (9.3 GB file)

🔧 Technical Details

Base Model: ibm-granite/granite-4.2-8b
Parameters: 8.8B (granite architecture)
Context Length: 128K tokens
Quantization: GGUF via llama.cpp (text generation)
Abliteration: Heretic v2.0.0.dev0 by p-e-w (Trial 158: 99→12 refusals @ KL 0.080)
License: Apache-2.0 (inherited from the base model)

⚠️ Disclaimer

This model has reduced safety guardrails. The removal of refusal behavior means it will engage with a wider range of prompts. Use responsibly and in accordance with applicable laws and regulations.

🙏 Acknowledgments

Base Model: IBM
Abliteration: Heretic by p-e-w
Quantization: llama.cpp

Built & maintained by Richard Young · DeepNeuro