huihui-ai/Huihui-Qwopus3.5-4B-v3-abliterated

VISIONConcurrent Unit Cost:1Model Size:4.5BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Apr 5, 2026License:apache-2.0Architecture:Transformer0.0K Open Weights Featherless Exclusive Cold

The huihui-ai/Huihui-Qwopus3.5-4B-v3-abliterated is a 4.5 billion parameter language model derived from Jackrong/Qwopus3.5-4B-v3. This model has undergone an 'abliteration' process to significantly reduce its safety filtering and refusal behaviors, making it an uncensored variant. It is primarily intended for research and experimental use in controlled environments where unfiltered content generation is desired.

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Overview

Huihui-Qwopus3.5-4B-v3-abliterated is a 4.5 billion parameter language model based on the Jackrong/Qwopus3.5-4B-v3 architecture. Its key distinguishing feature is the application of an "abliteration" technique, which aims to remove refusal behaviors and safety filtering present in the original model. This process, detailed in the remove-refusals-with-transformers project, results in a model capable of generating content without typical safety constraints.

Key Characteristics

  • Uncensored Output: Safety filtering has been significantly reduced, allowing for potentially sensitive, controversial, or inappropriate content generation.
  • Experimental Nature: Developed as a proof-of-concept for refusal removal without relying on TransformerLens.
  • Ollama Integration: Easily deployable via Ollama, with a pre-packaged version available for direct use.

Usage Considerations

Due to its uncensored nature, this model comes with several important warnings:

  • Risk of Sensitive Content: Users should be prepared for and rigorously review potentially inappropriate outputs.
  • Not for Public/Commercial Use: It is explicitly not recommended for public-facing commercial applications or environments requiring high security.
  • Legal and Ethical Responsibility: Users are solely responsible for ensuring their usage complies with all applicable laws and ethical standards.
  • Research Focus: Best suited for research, testing, or controlled experimental environments where the implications of unfiltered content are understood and managed.

Support

The developers welcome donations to support further development and improvements.