saidutta69/Qwen3.5-9B-heretic
saidutta69/Qwen3.5-9B-heretic is a decensored variant of the Qwen/Qwen3.5-9B model, created by saidutta69 using the Heretic v1.4.0 abliteration method. This 9 billion parameter model suppresses refusal behavior through targeted weight edits, leaving the base model's strong multilingual reasoning and agentic capabilities largely intact. It is designed for developers seeking Qwen's latest 9B model without built-in refusal guardrails, suitable for deployment on 12 GB GPUs or consumer hardware via GGUF quantizations.
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Overview
saidutta69/Qwen3.5-9B-heretic is a specialized variant of the Qwen/Qwen3.5-9B model, developed by saidutta69. This model has undergone a "decensoring" process using the Heretic v1.4.0 tool, which employs directional ablation (abliteration) to suppress refusal behaviors.
Key Differentiator: Abliteration
Unlike traditional fine-tuning, which can degrade coherence, abliteration directly edits specific weight directions responsible for refusal. This method ensures that the base model's core capabilities, such as its strong multilingual reasoning and agentic functions, remain largely untouched. The model is not a capability upgrade over the base Qwen3.5-9B but rather a modification to its refusal guardrails.
Capabilities & Use Cases
- Decensored Output: Deliberately designed to comply with requests that the base model would typically refuse, offering developers full control over model responses.
- Intact Base Capabilities: Retains the robust multilingual reasoning and agentic capabilities of the original Qwen3.5-9B.
- Hardware Compatibility: Optimized for deployment on 12 GB GPUs or consumer hardware using various GGUF quantizations (Q4_K_M, Q5_K_M, Q6_K, Q8_0).
- Developer-Focused: Ideal for developers who require a powerful 9B model without inherent safety filtering, taking full responsibility for its deployment and outputs.
Responsible Use
It is crucial to note that this model's refusal suppression is intentional. It will comply with requests that the base model would typically refuse, including potentially inappropriate ones. There are no additional safety filters layered on top, and users are responsible for the ethical deployment and use of this model.