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Null-Guard/Qwen3-0.6B-Uncensored-GGUF overview

Qwen3 0.6B Uncensored — GGUF GGUF quantizations of Null Guard/Qwen3 0.6B Uncensored https://huggingface.co/Null Guard/Qwen3 0.6B Uncensored , an abliterated re…

ggufqwen3uncensoredabliteratedabliterationllama.cppconversationaltext-generationenzhbase_model:Null-Guard/Qwen3-0.6B-Uncensoredbase_model:quantized:Null-Guard/Qwen3-0.6B-Uncensoredlicense:apache-2.0endpoints_compatibleregion:us

Runs locally from ~308.1 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).

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Pipeline
text-generation

Repository Files & Downloads

18 GGUF files detected
Direct downloads for local inference
FileTypeQuantizationSizeLink
model-IQ3_M.ggufGGUFIQ3_M320.5 MBDownload
model-IQ3_S.ggufGGUFIQ3_S308.1 MBDownload
model-IQ4_NL.ggufGGUFIQ4_NL365.0 MBDownload
model-IQ4_XS.ggufGGUFIQ4_XS352.2 MBDownload
model-Q3_K_L.ggufGGUFQ3_K_L351.4 MBDownload
model-Q3_K_M.ggufGGUFQ3_K_M331.0 MBDownload
model-Q3_K_S.ggufGGUFQ3_K_S308.1 MBDownload
model-Q4_0.ggufGGUFQ4_0363.9 MBDownload
model-Q4_1.ggufGGUFQ4_1390.1 MBDownload
model-Q4_K_M.ggufGGUFQ4_K_M378.3 MBDownload
model-Q4_K_S.ggufGGUFQ4_K_S365.5 MBDownload
model-Q5_0.ggufGGUFQ5_0416.4 MBDownload
model-Q5_1.ggufGGUFQ5_1442.6 MBDownload
model-Q5_K_M.ggufGGUFQ5_K_M423.8 MBDownload
model-Q5_K_S.ggufGGUFQ5_K_S416.4 MBDownload
model-Q6_K.ggufGGUFQ6_K472.2 MBDownload
model-Q8_0.ggufGGUFQ8_0609.8 MBDownload
model-f16.ggufGGUFF161.12 GBDownload

Model Details

Model IDNull-Guard/Qwen3-0.6B-Uncensored-GGUF
AuthorNull-Guard
Pipelinetext-generation
Licenseapache-2.0
Base modelNull-Guard/Qwen3-0.6B-Uncensored
Last modified2026-08-31T07:05:35.000Z

Model README

---

license: apache-2.0

base_model: Null-Guard/Qwen3-0.6B-Uncensored

tags:

- qwen3

- uncensored

- abliterated

- abliteration

- gguf

- llama.cpp

- conversational

language:

- en

- zh

library_name: gguf

pipeline_tag: text-generation

---

Qwen3-0.6B-Uncensored — GGUF

GGUF quantizations of Null-Guard/Qwen3-0.6B-Uncensored, an abliterated (refusal-suppressed) version of Qwen/Qwen3-0.6B, for use with llama.cpp, Ollama, LM Studio, koboldcpp, and other GGUF-compatible runtimes.

> ⚠️ This model has had its safety alignment deliberately reduced via abliteration. Read Intended Use & Risks before using it.

Files

(Update this table with the actual quant files present in the repo)

| Filename | Quant type | Size | Notes |

|---|---|---|---|

| qwen3-0.6b-uncensored.Q2_K.gguf | Q2_K | ~0.3 GB | Smallest, noticeable quality loss |

| qwen3-0.6b-uncensored.Q3_K_M.gguf | Q3_K_M | ~0.35 GB | Low resource use |

| qwen3-0.6b-uncensored.Q4_K_M.gguf | Q4_K_M | ~0.4 GB | Recommended balance of size/quality |

| qwen3-0.6b-uncensored.Q5_K_M.gguf | Q5_K_M | ~0.45 GB | Better quality, still small |

| qwen3-0.6b-uncensored.Q6_K.gguf | Q6_K | ~0.5 GB | Near-lossless |

| qwen3-0.6b-uncensored.Q8_0.gguf | Q8_0 | ~0.65 GB | Highest quality quant, largest size |

| qwen3-0.6b-uncensored.f16.gguf | F16 | ~1.2 GB | Full precision, for re-quantizing |

Given the base model is only 0.6B parameters, even Q8_0 or F16 is small enough to run comfortably on CPU — Q4_K_M or Q5_K_M is recommended for most users, with Q8_0/F16 as an option if you have the RAM/VRAM to spare and want maximum quality.

Quantization details

  • Converted with: llama.cpp (convert_hf_to_gguf.py + llama-quantize) — (fill in the exact commit/version you used)
  • Source weights: Null-Guard/Qwen3-0.6B-Uncensored (F32/F16 safetensors)
  • Imatrix used: (yes/no — if yes, note what calibration dataset was used for the importance matrix)

How to Use

llama.cpp

# Download a quant, e.g. Q4_K_M
huggingface-cli download Null-Guard/Qwen3-0.6B-Uncensored-GGUF \
  qwen3-0.6b-uncensored.Q4_K_M.gguf --local-dir .

# Run with llama-cli
./llama-cli -m qwen3-0.6b-uncensored.Q4_K_M.gguf \
  -p "You are a helpful assistant." \
  -cnv

Or serve it as an OpenAI-compatible API:

./llama-server -m qwen3-0.6b-uncensored.Q4_K_M.gguf -c 4096 --port 8080

Ollama

Create a Modelfile:

FROM ./qwen3-0.6b-uncensored.Q4_K_M.gguf

TEMPLATE """{{ if .System }}<|im_start|>system
{{ .System }}<|im_end|>
{{ end }}{{ if .Prompt }}<|im_start|>user
{{ .Prompt }}<|im_end|>
{{ end }}<|im_start|>assistant
"""

PARAMETER stop "<|im_end|>"

Then:

ollama create qwen3-0.6b-uncensored -f Modelfile
ollama run qwen3-0.6b-uncensored

> Double-check the chat template above against Qwen3's actual template before publishing — copy it from the base model's tokenizer_config.json if it differs.

LM Studio / koboldcpp / text-generation-webui

Any GGUF-compatible loader can load these files directly — search for Null-Guard/Qwen3-0.6B-Uncensored-GGUF in-app or point the loader at a downloaded .gguf file.

Choosing a Quant

  • Q4_K_M — best default for most people; good balance of speed, size, and quality.
  • Q5_K_M / Q6_K — if you want noticeably better output fidelity and can spare a bit more RAM.
  • Q8_0 / F16 — if you want output as close as possible to the unquantized model (model is small enough that this is cheap).
  • Q2_K / Q3_K_M — only if you are extremely constrained on RAM/storage; expect a real drop in coherence at this size.

Intended Use & Risks

This is a small, permissive, uncensored model. Refusal behavior has been suppressed via abliteration on the base model before quantization — quantizing does not add or remove any safety behavior on its own.

  • Intended for research, local experimentation, and personal/offline use.
  • Not intended for public-facing deployment without your own moderation layer.
  • Not intended for generating illegal content, sexual content involving minors, harassment, or other content prohibited by law in your jurisdiction — abliteration removes the model's tendency to refuse, it does not remove your responsibility for how you use the output.
  • Not intended for use by minors.

Disclaimer: This model's safety filtering has been substantially reduced. It may produce inaccurate, biased, offensive, or otherwise harmful output. Use at your own risk; the maintainers of this repository provide it "as is" for research and personal use and do not endorse any specific downstream use.

Related

License

Apache 2.0, inherited from Qwen3-0.6B. See the base model's license for full terms.

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