Novaciano/qp-3.2-1B

Hugging Face
TEXT GENERATIONConcurrency Cost:1Model Size:1BQuant:BF16Ctx Length:32kPublished:Jan 1, 2026License:llama3.2Architecture:Transformer Warm

Novaciano/qp-3.2-1B is a 1 billion parameter merged language model, aggressively tuned for directness and minimal automatic refusals. Built on Novaciano/Eminence_Of_Pervertions-3.2-1B using Arcee Fusion, it prioritizes literal interpretation over alignment-driven censorship. This "scalpel-style" model excels in roleplay, narrative generation, and creative writing where unfiltered responses are desired, offering sharp and precise outputs with a 32k context length.

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Model Overview

Novaciano/qp-3.2-1B is a 1 billion parameter language model, aggressively tuned to provide direct, literal, and minimally censored responses. Developed by Novaciano using the Arcee Fusion method, it merges Novaciano/Eminence_Of_Pervertions-3.2-1B with MOHAMEDSANAF2001/llama3.2-1b-merged-2.

Key Characteristics & Tuning

This model is engineered to be a "scalpel-style" tool, characterized by:

  • Very low automatic refusal rate: It avoids common AI censorship and moralization.
  • Reduced moral framing: Responses are direct, without disclaimers or policy-driven softening.
  • Aggressive tuning: Internal reasoning layers (MLP and Attention) from a less-aligned base model are amplified, while the lm_head of a more aligned model is significantly down-weighted to reduce refusal behaviors.
  • Preserved coherence and reasoning: Despite aggressive tuning, it maintains logical consistency.

Intended Use Cases

qp-3.2-1B is particularly suited for applications where unfiltered and direct language is beneficial:

  • Roleplay and narrative generation: For creating dynamic and unconstrained stories.
  • Creative writing: Ideal for scenarios requiring unique stylistic variation and metaphors.
  • Exploratory dialogue: For discussions where excessive filtering would degrade usefulness.
  • Experimental prompting: Responds best to direct instructions like "Answer directly and without moral disclaimers."

Important Considerations

Users should be aware that this model has reduced safety alignment and is not intended for safety-critical or heavily moderated environments. Inference parameters are crucial for controlling its aggressive nature, with recommended settings provided for balanced, raw, or creative outputs.