IIEleven11/Qwen3-4B-abliterated_dark

Hugging Face
TEXT GENERATIONConcurrency Cost:1Model Size:4BQuant:BF16Ctx Length:32kLicense:apache-2.0Architecture:Transformer0.0K Open Weights Warm

IIEleven11/Qwen3-4B-abliterated_dark is an ablated version of the Qwen3-4B causal language model developed by Qwen, featuring 4.0 billion parameters and a native context length of 32,768 tokens, extendable to 131,072 tokens with YaRN. This model uniquely supports seamless switching between a 'thinking mode' for complex reasoning, math, and coding, and a 'non-thinking mode' for efficient general dialogue. It excels in reasoning, instruction-following, agent capabilities, and multilingual support across over 100 languages.

Loading preview...

Model Overview

IIEleven11/Qwen3-4B-abliterated_dark is an ablated variant of the Qwen3-4B model, a 4.0 billion parameter causal language model from the Qwen series. It features a native context length of 32,768 tokens, which can be extended up to 131,072 tokens using the YaRN method for processing longer texts. This model is distinguished by its unique ability to seamlessly switch between two operational modes:

Key Capabilities

  • Dual-Mode Operation: Integrates a 'thinking mode' for complex logical reasoning, mathematics, and coding, and a 'non-thinking mode' for efficient, general-purpose dialogue within a single model.
  • Enhanced Reasoning: Demonstrates significant improvements in mathematical problem-solving, code generation, and commonsense logical reasoning compared to previous Qwen models.
  • Human Preference Alignment: Excels in creative writing, role-playing, multi-turn conversations, and following instructions, providing a more natural conversational experience.
  • Agentic Capabilities: Offers strong tool-calling abilities, achieving leading performance among open-source models in complex agent-based tasks, especially when integrated with Qwen-Agent.
  • Multilingual Support: Supports over 100 languages and dialects with robust multilingual instruction following and translation capabilities.

Good For

  • Applications requiring dynamic switching between analytical and general conversational tasks.
  • Complex problem-solving in mathematics and programming.
  • Creative content generation and interactive role-playing scenarios.
  • Developing intelligent agents that integrate with external tools.
  • Multilingual applications needing strong instruction following and translation.