vlx1/Qwen2.5-0.5B-Instruct-heretic
The vlx1/Qwen2.5-0.5B-Instruct-heretic is a 0.49 billion parameter instruction-tuned causal language model, derived from Qwen's Qwen2.5 series. This version is specifically decensored using Heretic v1.2.0, significantly reducing refusals compared to the original Qwen2.5-0.5B-Instruct model. It retains the base model's enhanced capabilities in coding, mathematics, long-text generation, and multilingual support across 29 languages, with a 32,768 token context length.
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vlx1/Qwen2.5-0.5B-Instruct-heretic: Decensored Qwen2.5 Model
This model is a decensored variant of the Qwen/Qwen2.5-0.5B-Instruct, created using the Heretic v1.2.0 tool. It significantly reduces model refusals, demonstrating 4 refusals out of 100 compared to 92/100 for the original model, while maintaining a low KL divergence of 0.0401.
Key Capabilities Inherited from Qwen2.5-0.5B-Instruct
- Enhanced Knowledge & Reasoning: Improved performance in coding and mathematics due to specialized expert models.
- Instruction Following: Stronger instruction adherence and resilience to diverse system prompts, beneficial for role-play and chatbot implementations.
- Long Context & Generation: Supports a full context length of 32,768 tokens and can generate up to 8,192 tokens.
- Structured Data & Output: Better at understanding structured data like tables and generating structured outputs, particularly JSON.
- Multilingual Support: Comprehensive support for over 29 languages, including major global languages.
Good For
- Applications requiring a less restrictive or decensored language model for instruction-following tasks.
- Use cases benefiting from strong coding and mathematical abilities in a compact 0.5 billion parameter model.
- Scenarios demanding long-context understanding and generation.
- Multilingual applications needing support for a wide array of languages.