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mradermacher/liujgoj-v1-qwen3-8b-base-i1-GGUF overview

About < quantize version: 2 < output tensor quantised: 1 < convert type: hf < vocab type: < tags: nicoboss < quants: Q2 K IQ3 M Q4 K S IQ3 XXS Q3 K M small IQ4…

transformersggufcantoneseorthographyliujgojspeech-firstcpttext-generationenbase_model:Yvthyvq/cantonese-qwen3-8b-basebase_model:quantized:Yvthyvq/cantonese-qwen3-8b-baselicense:apache-2.0endpoints_compatibleregion:usimatrixconversational

Runs locally from ~5.1 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).

Downloads
1,662
Likes
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Pipeline
text-generation

Repository Files & Downloads

25 GGUF files detected
Direct downloads for local inference
FileTypeQuantizationSizeLink
liujgoj-v1-qwen3-8b-base.i1-IQ1_M.ggufGGUFIQ1_M2.10 GBDownload
liujgoj-v1-qwen3-8b-base.i1-IQ1_S.ggufGGUFIQ1_S1.97 GBDownload
liujgoj-v1-qwen3-8b-base.i1-IQ2_M.ggufGGUFIQ2_M2.84 GBDownload
liujgoj-v1-qwen3-8b-base.i1-IQ2_S.ggufGGUFIQ2_S2.67 GBDownload
liujgoj-v1-qwen3-8b-base.i1-IQ2_XS.ggufGGUFIQ2_XS2.51 GBDownload
liujgoj-v1-qwen3-8b-base.i1-IQ2_XXS.ggufGGUFIQ2_XXS2.32 GBDownload
liujgoj-v1-qwen3-8b-base.i1-IQ3_M.ggufGGUFIQ3_M3.63 GBDownload
liujgoj-v1-qwen3-8b-base.i1-IQ3_S.ggufGGUFIQ3_S3.53 GBDownload
liujgoj-v1-qwen3-8b-base.i1-IQ3_XS.ggufGGUFIQ3_XS3.38 GBDownload
liujgoj-v1-qwen3-8b-base.i1-IQ3_XXS.ggufGGUFIQ3_XXS3.14 GBDownload
liujgoj-v1-qwen3-8b-base.i1-IQ4_NL.ggufGGUFIQ4_NL4.46 GBDownload
liujgoj-v1-qwen3-8b-base.i1-IQ4_XS.ggufGGUFIQ4_XS4.25 GBDownload
liujgoj-v1-qwen3-8b-base.i1-Q2_K.ggufGGUFQ2_K3.06 GBDownload
liujgoj-v1-qwen3-8b-base.i1-Q2_K_S.ggufGGUFQ2_K_S2.87 GBDownload
liujgoj-v1-qwen3-8b-base.i1-Q3_K_L.ggufGGUFQ3_K_L4.13 GBDownload
liujgoj-v1-qwen3-8b-base.i1-Q3_K_M.ggufGGUFQ3_K_M3.84 GBDownload
liujgoj-v1-qwen3-8b-base.i1-Q3_K_S.ggufGGUFQ3_K_S3.51 GBDownload
liujgoj-v1-qwen3-8b-base.i1-Q4_0.ggufGGUFQ4_04.46 GBDownload
liujgoj-v1-qwen3-8b-base.i1-Q4_1.ggufGGUFQ4_14.89 GBDownload
liujgoj-v1-qwen3-8b-base.i1-Q4_K_M.ggufGGUFQ4_K_M4.68 GBDownload
liujgoj-v1-qwen3-8b-base.i1-Q4_K_S.ggufGGUFQ4_K_S4.47 GBDownload
liujgoj-v1-qwen3-8b-base.i1-Q5_K_M.ggufGGUFQ5_K_M5.45 GBDownload
liujgoj-v1-qwen3-8b-base.i1-Q5_K_S.ggufGGUFQ5_K_S5.33 GBDownload
liujgoj-v1-qwen3-8b-base.i1-Q6_K.ggufGGUFQ6_K6.26 GBDownload
liujgoj-v1-qwen3-8b-base.imatrix.ggufGGUFGGUF5.1 MBDownload

Model Details

Model IDmradermacher/liujgoj-v1-qwen3-8b-base-i1-GGUF
Authormradermacher
Pipelinetext-generation
Licenseapache-2.0
Base modelYvthyvq/cantonese-qwen3-8b-base
Last modified2026-06-07T07:18:14.000Z

Model README

---

base_model: Yvthyvq/cantonese-qwen3-8b-base

language:

  • en

library_name: transformers

license: apache-2.0

mradermacher:

readme_rev: 1

quantized_by: mradermacher

tags:

  • cantonese
  • orthography
  • liujgoj
  • speech-first
  • cpt
  • text-generation

---

About

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

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

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

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

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

<!-- ### quants: Q2_K IQ3_M Q4_K_S IQ3_XXS Q3_K_M small-IQ4_NL Q4_K_M IQ2_M Q6_K IQ4_XS Q2_K_S IQ1_M Q3_K_S IQ2_XXS Q3_K_L IQ2_XS Q5_K_S IQ2_S IQ1_S Q5_K_M Q4_0 IQ3_XS Q4_1 IQ3_S -->

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

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

weighted/imatrix quants of https://huggingface.co/Yvthyvq/cantonese-qwen3-8b-base

<!-- provided-files -->

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

static quants are available at https://huggingface.co/mradermacher/liujgoj-v1-qwen3-8b-base-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 | imatrix | 0.1 | imatrix file (for creating your own quants) |

| GGUF | i1-IQ1_S | 2.2 | for the desperate |

| GGUF | i1-IQ1_M | 2.4 | mostly desperate |

| GGUF | i1-IQ2_XXS | 2.6 | |

| GGUF | i1-IQ2_XS | 2.8 | |

| GGUF | i1-IQ2_S | 3.0 | |

| GGUF | i1-IQ2_M | 3.2 | |

| GGUF | i1-Q2_K_S | 3.2 | very low quality |

| GGUF | i1-Q2_K | 3.4 | IQ3_XXS probably better |

| GGUF | i1-IQ3_XXS | 3.5 | lower quality |

| GGUF | i1-IQ3_XS | 3.7 | |

| GGUF | i1-Q3_K_S | 3.9 | IQ3_XS probably better |

| GGUF | i1-IQ3_S | 3.9 | beats Q3_K* |

| GGUF | i1-IQ3_M | 4.0 | |

| GGUF | i1-Q3_K_M | 4.2 | IQ3_S probably better |

| GGUF | i1-Q3_K_L | 4.5 | IQ3_M probably better |

| GGUF | i1-IQ4_XS | 4.7 | |

| GGUF | i1-Q4_0 | 4.9 | fast, low quality |

| GGUF | i1-IQ4_NL | 4.9 | prefer IQ4_XS |

| GGUF | i1-Q4_K_S | 4.9 | optimal size/speed/quality |

| GGUF | i1-Q4_K_M | 5.1 | fast, recommended |

| GGUF | i1-Q4_1 | 5.3 | |

| GGUF | i1-Q5_K_S | 5.8 | |

| GGUF | i1-Q5_K_M | 6.0 | |

| GGUF | i1-Q6_K | 6.8 | practically like static Q6_K |

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. Additional thanks to @nicoboss for giving me access to his private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to.

<!-- end -->

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