πŸ“‹ Model Description


license: apache-2.0 base_model:
  • huihui-ai/Huihui-Qwen3-4B-Thinking-2507-abliterated
  • huihui-ai/Huihui-Qwen3-4B-Instruct-2507-abliterated
language:
  • en
pipeline_tag: text-generation library_name: transformers tags:
  • text-generation-inference

Qwen3-4B-2507-abliterated-GGUF

The Huihui-Qwen3-4B-Instruct-2507-abliterated model is an uncensored, proof-of-concept version of the Qwen3-4B-Instruct-2507 large language model, created using a novel abliteration method designed to remove refusal responses without using TransformerLens. This approach offers a faster and more effective way to bypass the model's standard refusal behaviors, resulting in a less filtered and more raw output experience, though it lacks rigorous safety filtering and may generate sensitive or controversial content. The model is quantized (4-bit) for efficient use, can be used directly in Hugging Face’s transformers library, and is intended primarily for research or experimental use rather than production due to the reduced content restrictions and associated risks. Users are advised to carefully monitor outputs and ensure ethical and legal compliance when deploying this model.

Qwen3-4B-2507-abliterated-GGUF (GGUF Formats)

Model VariantLink
Qwen3-4B-Thinking-2507-abliterated-GGUFHugging Face
Qwen3-4B-Instruct-2507-abliterated-GGUFHugging Face

Model Files

Qwen3-4B-Thinking-2507-abliterated

File NameSizeQuant Type
Qwen3-4B-Thinking-2507-abliterated.BF16.gguf8.05 GBBF16
Qwen3-4B-Thinking-2507-abliterated.F16.gguf8.05 GBF16
Qwen3-4B-Thinking-2507-abliterated.F32.gguf16.1 GBF32
Qwen3-4B-Thinking-2507-abliterated.Q2K.gguf1.67 GBQ2K
Qwen3-4B-Thinking-2507-abliterated.Q3KL.gguf2.24 GBQ3KL
Qwen3-4B-Thinking-2507-abliterated.Q3KM.gguf2.08 GBQ3KM
Qwen3-4B-Thinking-2507-abliterated.Q3KS.gguf1.89 GBQ3KS
Qwen3-4B-Thinking-2507-abliterated.Q4KM.gguf2.5 GBQ4KM
Qwen3-4B-Thinking-2507-abliterated.Q4KS.gguf2.38 GBQ4KS
Qwen3-4B-Thinking-2507-abliterated.Q5KM.gguf2.89 GBQ5KM
Qwen3-4B-Thinking-2507-abliterated.Q5KS.gguf2.82 GBQ5KS
Qwen3-4B-Thinking-2507-abliterated.Q6K.gguf3.31 GBQ6K
Qwen3-4B-Thinking-2507-abliterated.Q80.gguf4.28 GBQ80

Qwen3-4B-Instruct-2507-abliterated

File NameSizeQuant Type
Qwen3-4B-Instruct-2507-abliterated.BF16.gguf8.05 GBBF16
Qwen3-4B-Instruct-2507-abliterated.F16.gguf8.05 GBF16
Qwen3-4B-Instruct-2507-abliterated.F32.gguf16.1 GBF32
Qwen3-4B-Instruct-2507-abliterated.Q2K.gguf1.67 GBQ2K
Qwen3-4B-Instruct-2507-abliterated.Q3KL.gguf2.24 GBQ3KL
Qwen3-4B-Instruct-2507-abliterated.Q3KM.gguf2.08 GBQ3KM
Qwen3-4B-Instruct-2507-abliterated.Q3KS.gguf1.89 GBQ3KS
Qwen3-4B-Instruct-2507-abliterated.Q4KM.gguf2.5 GBQ4KM
Qwen3-4B-Instruct-2507-abliterated.Q4KS.gguf2.38 GBQ4KS
Qwen3-4B-Instruct-2507-abliterated.Q5KM.gguf2.89 GBQ5KM
Qwen3-4B-Instruct-2507-abliterated.Q5KS.gguf2.82 GBQ5KS
Qwen3-4B-Instruct-2507-abliterated.Q6K.gguf3.31 GBQ6K
Qwen3-4B-Instruct-2507-abliterated.Q80.gguf4.28 GBQ80

Quants Usage

(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)

Here is a handy graph by ikawrakow comparing some lower-quality quant
types (lower is better):

!image.png

πŸ“‚ GGUF File List

No GGUF files available