DreamFast/qwen3-4b-heretic
DreamFast/qwen3-4b-heretic is a 4 billion parameter language model based on Qwen 3 4B, modified using the Heretic v1.2.0 tool. This model features significantly reduced refusal rates (3/100 compared to 100/100 for the original) with zero measurable KL divergence, indicating no loss in model quality. It is primarily designed as an uncensored text encoder for image generation models like Z-Image and FLUX.2 Klein 4B, offering enhanced creative freedom.
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Qwen 3 4B - Heretic (Abliterated)
DreamFast/qwen3-4b-heretic is an abliterated version of the Qwen 3 4B model, processed with the Heretic v1.2.0 tool. This modification significantly reduces the model's tendency to refuse prompts, making it a more open and versatile text encoder. The abliteration process was carefully conducted over 200 trials, with Trial 96 selected for achieving a refusal rate of only 3 out of 100 prompts, while maintaining a KL divergence of 0.0000, indicating no measurable damage to the model's original capabilities.
Key Capabilities
- Reduced Refusals: Achieves a refusal rate of 3/100, a substantial reduction from the base model's 100/100, enabling more direct and uncensored outputs.
- Preserved Quality: Zero measurable KL divergence ensures that the core quality and performance of the original Qwen 3 4B model are retained.
- Optimized for Image Generation: Specifically tailored to function as an uncensored text encoder for advanced image generation models such as Z-Image and FLUX.2 Klein 4B.
- Flexible Formats: Available in HuggingFace, ComfyUI (bf16, fp8, nvfp4), and GGUF (F16, Q8_0, Q6_K, Q5_K_M, Q4_K_M, Q3_K_M) formats for broad compatibility.
Good for
- Uncensored Text Encoding: Ideal for users requiring a text encoder with minimal content restrictions for creative applications.
- Image Generation Workflows: Excellent for integration into ComfyUI-based image generation pipelines, particularly with Z-Image and FLUX.2 Klein 4B.
- Resource-Efficient Deployment: Offers various quantized GGUF and ComfyUI formats (e.g., NVFP4 at 2.6GB) for efficient deployment on diverse hardware, including older GPUs via software dequantization.