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fairy322/Huihui-Qwen3.5-9B-abliterated-TIES-Hemlock-SFT-GGUF overview

About < quantize version: 2 < output tensor quantised: 1 < convert type: hf < vocab type: < tags: < quants: x f16 Q4 K S Q2 K Q8 0 Q6 K Q3 K M Q3 K S Q3 K L Q4…

transformersggufmerlinagrimoiretext-generationsftendataset:hemlang/Hemlock-SFTbase_model:nbeerbower/Huihui-Qwen3.5-9B-abliterated-TIES-Hemlock-SFTbase_model:quantized:nbeerbower/Huihui-Qwen3.5-9B-abliterated-TIES-Hemlock-SFTendpoints_compatibleregion:usconversational

Runs locally from ~3.56 GB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).

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Pipeline
text-generation
Author

Repository Files & Downloads

12 GGUF files detected
Direct downloads for local inference
FileTypeQuantizationSizeLink
Huihui-Qwen3.5-9B-abliterated-TIES-Hemlock-SFT.IQ4_XS.ggufGGUFGGUF4.87 GBDownload
Huihui-Qwen3.5-9B-abliterated-TIES-Hemlock-SFT.Q2_K.ggufGGUFGGUF3.56 GBDownload
Huihui-Qwen3.5-9B-abliterated-TIES-Hemlock-SFT.Q3_K_L.ggufGGUFGGUF4.59 GBDownload
Huihui-Qwen3.5-9B-abliterated-TIES-Hemlock-SFT.Q3_K_M.ggufGGUFGGUF4.31 GBDownload
Huihui-Qwen3.5-9B-abliterated-TIES-Hemlock-SFT.Q3_K_S.ggufGGUFGGUF3.97 GBDownload
Huihui-Qwen3.5-9B-abliterated-TIES-Hemlock-SFT.Q4_K_M.ggufGGUFGGUF5.24 GBDownload
Huihui-Qwen3.5-9B-abliterated-TIES-Hemlock-SFT.Q4_K_S.ggufGGUFGGUF4.98 GBDownload
Huihui-Qwen3.5-9B-abliterated-TIES-Hemlock-SFT.Q5_K_M.ggufGGUFGGUF6.02 GBDownload
Huihui-Qwen3.5-9B-abliterated-TIES-Hemlock-SFT.Q5_K_S.ggufGGUFGGUF5.87 GBDownload
Huihui-Qwen3.5-9B-abliterated-TIES-Hemlock-SFT.Q6_K.ggufGGUFGGUF6.85 GBDownload
Huihui-Qwen3.5-9B-abliterated-TIES-Hemlock-SFT.Q8_0.ggufGGUFGGUF8.87 GBDownload
Huihui-Qwen3.5-9B-abliterated-TIES-Hemlock-SFT.f16.ggufGGUFGGUF16.69 GBDownload

Model Details

Model IDfairy322/Huihui-Qwen3.5-9B-abliterated-TIES-Hemlock-SFT-GGUF
Authorfairy322
Pipelinetext-generation
License
Base modelnbeerbower/Huihui-Qwen3.5-9B-abliterated-TIES-Hemlock-SFT
Last modified2026-08-08T04:18:45.000Z

Model README

---

base_model: nbeerbower/Huihui-Qwen3.5-9B-abliterated-TIES-Hemlock-SFT

datasets:

  • hemlang/Hemlock-SFT

language:

  • en

library_name: transformers

mradermacher:

readme_rev: 1

quantized_by: mradermacher

tags:

  • merlina
  • grimoire
  • text-generation
  • sft

---

About

<!-- ### quantize_version: 2 -->

<!-- ### output_tensor_quantised: 1 -->

<!-- ### convert_type: hf -->

<!-- ### vocab_type: -->

<!-- ### tags: -->

<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->

<!-- ### quants_skip: -->

<!-- ### skip_mmproj: 1 -->

static quants of https://huggingface.co/nbeerbower/Huihui-Qwen3.5-9B-abliterated-TIES-Hemlock-SFT

<!-- provided-files -->

For a convenient overview and download list, visit our model page for this model.

weighted/imatrix quants are available at https://huggingface.co/mradermacher/Huihui-Qwen3.5-9B-abliterated-TIES-Hemlock-SFT-i1-GGUF

Usage

If you are unsure how to use GGUF files, refer to one of [TheBloke's

READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for

more details, including on how to concatenate multi-part files.

Provided Quants

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

| Link | Type | Size/GB | Notes |

|:-----|:-----|--------:|:------|

| GGUF | Q2_K | 3.9 | |

| GGUF | Q3_K_S | 4.4 | |

| GGUF | Q3_K_M | 4.7 | lower quality |

| GGUF | Q3_K_L | 5.0 | |

| GGUF | IQ4_XS | 5.3 | |

| GGUF | Q4_K_S | 5.5 | fast, recommended |

| GGUF | Q4_K_M | 5.7 | fast, recommended |

| GGUF | Q5_K_S | 6.4 | |

| GGUF | Q5_K_M | 6.6 | |

| GGUF | Q6_K | 7.5 | very good quality |

| GGUF | Q8_0 | 9.6 | fast, best quality |

| GGUF | f16 | 18.0 | 16 bpw, overkill |

Here is a handy graph by ikawrakow comparing some lower-quality quant

types (lower is better):

!image.png

And here are Artefact2's thoughts on the matter:

https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9

FAQ / Model Request

See https://huggingface.co/mradermacher/model_requests for some answers to

questions you might have and/or if you want some other model quantized.

Thanks

I thank my company, nethype GmbH, for letting

me use its servers and providing upgrades to my workstation to enable

this work in my free time.

<!-- end -->

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