Model Overview
DavidAU/Gemma3-27B-it-vl-GLM-4.7-Uncensored-Heretic-Deep-Reasoning is a 27 billion parameter Gemma 3 instruction-tuned model, enhanced with deep reasoning capabilities. It leverages the GLM 4.7 reasoning dataset and Unsloth for fine-tuning, resulting in a fully uncensored model designed to provide direct and detailed responses without refusal.
Key Capabilities & Features
- Deep Reasoning: Significantly improves image "intelligence" and general model operation, leading to enhanced output generation and benchmark performance.
- Uncensored Output: Designed to generate content exactly as requested, including explicit or sensitive topics, with minimal refusal. It may require specific directives (e.g., "use these words to swear") for highly graphic content.
- Extended Context: Features a 128k context window, allowing for processing longer inputs and maintaining coherence.
- Temperature Stability: Reasoning capabilities remain stable across a wide temperature range (0.1 to 2.5).
- Optional Thinking Activation: Users can explicitly activate deeper thinking with "think deeply: prompt" or by using specialized Jinja templates for always-on thinking.
Performance & Benchmarks
The model demonstrates improved benchmark scores compared to its non-thinking predecessor, Gemma-3-27b-it-heretic, across various tasks like arc_challenge, arc_easy, boolq, hellaswag, piqa, and winogrande.
Decensoring Statistics
With a KL divergence of 0.07 (compared to 0 for the original model) and only 9 refusals out of 100, this model maintains high fidelity to the original while significantly reducing content refusals.
Recommended Use Cases
This model is suitable for applications requiring:
- Direct and Unfiltered Responses: Ideal for use cases where content filtering or refusal is undesirable.
- Enhanced Reasoning: Beneficial for tasks demanding complex problem-solving, detailed analysis, or improved understanding of visual inputs.
- Creative and Roleplay Scenarios: Its uncensored nature and reasoning capabilities make it well-suited for generating diverse and specific narrative content.