roslein/Qwen3-32B-abliterated
Hugging Face
TEXT GENERATIONConcurrency Cost:2Model Size:32BQuant:FP8Ctx Length:32kPublished:May 2, 2025License:apache-2.0Architecture:Transformer0.0K Open Weights Warm

The roslein/Qwen3-32B-abliterated model is a 32.8 billion parameter causal language model based on the Qwen3 architecture, featuring 64 layers and GQA. This version has undergone an "abliteration" process using proportional scaling to reduce refusal behavior while preserving some safety guardrails. It offers a balance between responsiveness and safety, making it suitable for research and applications where slight quality degradation is acceptable for broader response generation.

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Qwen3-32B Abliterated Model Overview

This model, roslein/Qwen3-32B-abliterated, is a 32.8 billion parameter causal language model derived from the Qwen3 architecture. It features 64 layers with 64 query attention heads and 8 key-value heads (GQA), and supports a native context length of 32,768 tokens, extendable to 131,072 tokens with YaRN.

Key Characteristics

The primary differentiator of this model is its "abliteration" process, which uses a proportional scaling technique to apply varying abliteration strengths across different layers. This process aims to reduce the model's refusal behavior while attempting to preserve overall quality.

  • Reduced Refusal Behavior: The model is designed to be more open to responding to a wider range of prompts, though it still retains some safety guardrails for harmful requests.
  • Quality Trade-off: While refusal behavior is reduced, there is a minor degradation in quality, particularly noted in responses for less common languages, nuanced reasoning tasks, and complex instruction following.

Recommended Use Cases

This abliterated model is positioned as a middle ground between strict safety and broad capability, making it suitable for:

  • Research: Ideal for studies where reduced refusal behavior is beneficial for exploring model responses.
  • Applications with Balanced Safety: Useful in scenarios where some safety guardrails are still desired, but a more permissive response generation is preferred.
  • Acceptable Quality Degradation: Suited for use cases where the slight impact on quality is an acceptable trade-off for increased responsiveness.
Popular Sampler Settings

Top 3 parameter combinations used by Featherless users for this model. Click a tab to see each config.

temperature
top_p
top_k
frequency_penalty
presence_penalty
repetition_penalty
min_p