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prithivMLmods/Qwen3-4B-2507-abliterated-GGUF
Qwen3-4B-2507-abliterated-GGUF is a text generation model from prithivMLmods. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as apache-2.0.
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 r…
Downloads · 30 days
3.3K
3% of all-time downloads
All-time downloads
100K
Public
Repo size
117 GB
Likes
14
Public
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.gguf117 GB · 100%
From the Hugging Face model README
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.
| Model Variant | Link |
|---|---|
| Qwen3-4B-Thinking-2507-abliterated-GGUF | Hugging Face |
| Qwen3-4B-Instruct-2507-abliterated-GGUF | Hugging Face |
| 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 |
| 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 |
(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):
