Hugging Face Model Overview
coder3101/gemma-3-27b-it-heretic-v2 is a 27 billion parameter instruction-tuned multimodal language model, a modified version of Google's Gemma 3-27b-it. This model has been 'decensored' using the Heretic tool, resulting in a substantial reduction in refusal rates (14/100 compared to the original model's 98/100). It maintains the core capabilities of the Gemma 3 family, which are built from the same research and technology as the Gemini models.
Key Capabilities
- Multimodal Input: Handles both text and image inputs, with images normalized to 896x896 resolution and encoded to 256 tokens each.
- Extensive Context: Features a large 32K token context window for the 27B variant, enabling processing of longer inputs.
- Multilingual Support: Supports over 140 languages for text generation.
- Reduced Refusals: Significantly less prone to refusing prompts compared to its base model, making it suitable for a wider range of applications.
- General Purpose: Capable of various text generation and image understanding tasks, including question answering, summarization, and reasoning.
Should I use this for my use case?
This model is particularly suited for developers who require a powerful multimodal LLM with a large context window and a significantly reduced tendency to refuse prompts. If your application involves creative content generation, open-ended dialogue, or tasks where the original Gemma 3 model's content filtering was too restrictive, this 'heretic' version offers greater flexibility. It is ideal for scenarios demanding less constrained responses, while still leveraging the strong foundational capabilities of the Gemma 3 architecture in reasoning, STEM, and multilingual tasks.