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---
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](https://huggingface.co/collections/huihui-ai/qwen3-abliterated-6810edc9f3bd663630b64ab7) 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 Variant | Link |
|--------------|------|
| **Qwen3-4B-Thinking-2507-abliterated-GGUF** | [Hugging Face](https://huggingface.co/prithivMLmods/Qwen3-4B-2507-abliterated-GGUF/tree/main/Qwen3-4B-Thinking-2507-abliterated-GGUF) |
| **Qwen3-4B-Instruct-2507-abliterated-GGUF** | [Hugging Face](https://huggingface.co/prithivMLmods/Qwen3-4B-2507-abliterated-GGUF/tree/main/Qwen3-4B-Instruct-2507-abliterated-GGUF) |
# Model Files
## Qwen3-4B-Thinking-2507-abliterated
| File Name | Size | Quant Type |
|-----------|------|------------|
| Qwen3-4B-Thinking-2507-abliterated.BF16.gguf | 8.05 GB | BF16 |
| Qwen3-4B-Thinking-2507-abliterated.F16.gguf | 8.05 GB | F16 |
| Qwen3-4B-Thinking-2507-abliterated.F32.gguf | 16.1 GB | F32 |
| Qwen3-4B-Thinking-2507-abliterated.Q2_K.gguf | 1.67 GB | Q2_K |
| Qwen3-4B-Thinking-2507-abliterated.Q3_K_L.gguf | 2.24 GB | Q3_K_L |
| Qwen3-4B-Thinking-2507-abliterated.Q3_K_M.gguf | 2.08 GB | Q3_K_M |
| Qwen3-4B-Thinking-2507-abliterated.Q3_K_S.gguf | 1.89 GB | Q3_K_S |
| Qwen3-4B-Thinking-2507-abliterated.Q4_K_M.gguf | 2.5 GB | Q4_K_M |
| Qwen3-4B-Thinking-2507-abliterated.Q4_K_S.gguf | 2.38 GB | Q4_K_S |
| Qwen3-4B-Thinking-2507-abliterated.Q5_K_M.gguf | 2.89 GB | Q5_K_M |
| Qwen3-4B-Thinking-2507-abliterated.Q5_K_S.gguf | 2.82 GB | Q5_K_S |
| Qwen3-4B-Thinking-2507-abliterated.Q6_K.gguf | 3.31 GB | Q6_K |
| Qwen3-4B-Thinking-2507-abliterated.Q8_0.gguf | 4.28 GB | Q8_0 |
## Qwen3-4B-Instruct-2507-abliterated
| File Name | Size | Quant Type |
|-----------|------|------------|
| Qwen3-4B-Instruct-2507-abliterated.BF16.gguf | 8.05 GB | BF16 |
| Qwen3-4B-Instruct-2507-abliterated.F16.gguf | 8.05 GB | F16 |
| Qwen3-4B-Instruct-2507-abliterated.F32.gguf | 16.1 GB | F32 |
| Qwen3-4B-Instruct-2507-abliterated.Q2_K.gguf | 1.67 GB | Q2_K |
| Qwen3-4B-Instruct-2507-abliterated.Q3_K_L.gguf | 2.24 GB | Q3_K_L |
| Qwen3-4B-Instruct-2507-abliterated.Q3_K_M.gguf | 2.08 GB | Q3_K_M |
| Qwen3-4B-Instruct-2507-abliterated.Q3_K_S.gguf | 1.89 GB | Q3_K_S |
| Qwen3-4B-Instruct-2507-abliterated.Q4_K_M.gguf | 2.5 GB | Q4_K_M |
| Qwen3-4B-Instruct-2507-abliterated.Q4_K_S.gguf | 2.38 GB | Q4_K_S |
| Qwen3-4B-Instruct-2507-abliterated.Q5_K_M.gguf | 2.89 GB | Q5_K_M |
| Qwen3-4B-Instruct-2507-abliterated.Q5_K_S.gguf | 2.82 GB | Q5_K_S |
| Qwen3-4B-Instruct-2507-abliterated.Q6_K.gguf | 3.31 GB | Q6_K |
| Qwen3-4B-Instruct-2507-abliterated.Q8_0.gguf | 4.28 GB | Q8_0 |
## 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](https://www.nethype.de/huggingface_embed/quantpplgraph.png)

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{
"model_type": "qwen3"
}