DavidAU/Qwen3.5-27B-HERETIC-Polaris-Advanced-Thinking-Alpha-uncensored
The DavidAU/Qwen3.5-27B-HERETIC-Polaris-Advanced-Thinking-Alpha-uncensored is a 27 billion parameter Qwen 3.5 dense model fine-tuned by DavidAU using the POLARIS distill dataset. This model features altered reasoning/thinking blocks and is a "HERETIC" model, designed to follow instructions without refusal. It supports vision inputs and maintains strong benchmarks while offering reduced safety alignment.
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Model Overview
This model, DavidAU/Qwen3.5-27B-HERETIC-Polaris-Advanced-Thinking-Alpha-uncensored, is a 27 billion parameter Qwen 3.5 dense model fine-tuned by DavidAU. It incorporates a unique "HERETIC" training approach, significantly reducing safety alignment and refusals (14/100 compared to 94/100 for the original Qwen3.5-27B). The fine-tuning process also altered its reasoning/thinking blocks and their size, aiming for enhanced instruction following.
Key Capabilities
- Uncensored Instruction Following: Designed to execute commands without refusal, offering greater flexibility for developers.
- Vision-Language Support: Tested and confirmed working with image inputs, leveraging the base Qwen3.5's unified vision-language foundation.
- Altered Reasoning Architecture: Features modified internal reasoning mechanisms for potentially different response generation.
- Strong Benchmark Retention: Despite modifications, efforts were made to preserve the strong performance of the base Qwen3.5 model across various benchmarks.
- Multilingual Support: Inherits Qwen3.5's expanded support for 201 languages and dialects.
- Long Context: Supports a native context length of 262,144 tokens, extensible up to 1,010,000 tokens with YaRN scaling.
Good for
- Unrestricted Content Generation: Ideal for applications requiring responses without built-in safety filters or refusals.
- Advanced Reasoning Tasks: Potentially beneficial for tasks where modified thinking blocks could offer novel approaches.
- Multimodal Applications: Suitable for tasks involving both text and image inputs.
- Developers requiring maximum control: Offers a model that prioritizes user instructions over inherent safety alignments.