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mradermacher/gugugo-koen-7b-v1.1-i1-gguf IQ3_XXS GGUF - Free GGUF Download is indexed on GraySoft with repository links, GGUF quant files, and Hugging Face metadata. This page helps you pick a local model for guIDE or other runtimes. See related models in the same shard below.

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mradermacher/gugugo-koen-7b-v1.1-i1-gguf overview

About weighted/imatrix quants of https://huggingface.co/squarelike/Gugugo-koen-7B-V1.1 static quants are available at https://huggingface.co/mradermacher/Gugugo-koen-7B-V1.1-GGUF

transformersggufenkodataset:squarelike/sharegpt_deepl_ko_translationbase_model:squarelike/Gugugo-koen-7B-V1.1base_model:quantized:squarelike/Gugugo-koen-7B-V1.1license:apache-2.0endpoints_compatibleregion:usimatrix
mradermacher/gugugo-koen-7b-v1.1-i1-gguf visual
Downloads
115
Likes
0
Pipeline
Library
transformers
Visibility
Public
Access
Open

Repository Files & Downloads

25 files detected
Direct downloads for all repository files
FileTypeQuantizationSizeLink
Gugugo-koen-7B-V1.1.i1-IQ1_M.gguf GGUF IQ1_M 1.59 GB Download
Gugugo-koen-7B-V1.1.i1-IQ1_S.gguf GGUF IQ1_S 1.48 GB Download
Gugugo-koen-7B-V1.1.i1-IQ2_M.gguf GGUF IQ2_M 2.26 GB Download
Gugugo-koen-7B-V1.1.i1-IQ2_S.gguf GGUF IQ2_S 2.11 GB Download
Gugugo-koen-7B-V1.1.i1-IQ2_XS.gguf GGUF IQ2_XS 1.95 GB Download
Gugugo-koen-7B-V1.1.i1-IQ2_XXS.gguf GGUF IQ2_XXS 1.78 GB Download
Gugugo-koen-7B-V1.1.i1-IQ3_M.gguf GGUF IQ3_M 2.97 GB Download
Gugugo-koen-7B-V1.1.i1-IQ3_S.gguf GGUF IQ3_S 2.81 GB Download
Gugugo-koen-7B-V1.1.i1-IQ3_XS.gguf GGUF IQ3_XS 2.67 GB Download
Gugugo-koen-7B-V1.1.i1-IQ3_XXS.gguf GGUF IQ3_XXS 2.47 GB Download
Gugugo-koen-7B-V1.1.i1-IQ4_XS.gguf GGUF IQ4_XS 3.45 GB Download
Gugugo-koen-7B-V1.1.i1-Q2_K.gguf GGUF Q2_K 2.42 GB Download
Gugugo-koen-7B-V1.1.i1-Q2_K_S.gguf GGUF Q2_K_S 2.22 GB Download
Gugugo-koen-7B-V1.1.i1-Q3_K_L.gguf GGUF Q3_K_L 3.42 GB Download
Gugugo-koen-7B-V1.1.i1-Q3_K_M.gguf GGUF Q3_K_M 3.14 GB Download
Gugugo-koen-7B-V1.1.i1-Q3_K_S.gguf GGUF Q3_K_S 2.81 GB Download
Gugugo-koen-7B-V1.1.i1-Q4_0.gguf GGUF 3.65 GB Download
Gugugo-koen-7B-V1.1.i1-Q4_0_4_4.gguf GGUF 3.64 GB Download
Gugugo-koen-7B-V1.1.i1-Q4_0_4_8.gguf GGUF 3.64 GB Download
Gugugo-koen-7B-V1.1.i1-Q4_0_8_8.gguf GGUF 3.64 GB Download
Gugugo-koen-7B-V1.1.i1-Q4_K_M.gguf GGUF Q4_K_M 3.88 GB Download
Gugugo-koen-7B-V1.1.i1-Q4_K_S.gguf GGUF Q4_K_S 3.67 GB Download
Gugugo-koen-7B-V1.1.i1-Q5_K_M.gguf GGUF Q5_K_M 4.54 GB Download
Gugugo-koen-7B-V1.1.i1-Q5_K_S.gguf GGUF Q5_K_S 4.42 GB Download
Gugugo-koen-7B-V1.1.i1-Q6_K.gguf GGUF Q6_K 5.24 GB Download

Model Details Live

Model Slug
mradermacher/gugugo-koen-7b-v1.1-i1-gguf
Author
mradermacher
Pipeline Task
Library
transformers
Created
2024-12-07
Last Modified
2024-12-08
Gated
No
Private
No
HF SHA
d67266bca46a99c7d580a8964263a4a04004332d
License
apache-2.0
Language
en, ko
Base Model
squarelike/Gugugo-koen-7B-V1.1

Metadata Inspector

Normalized metadata (stored in metadata_json)
{
  "metadata": {},
  "card_data": {
    "base_model": "squarelike/Gugugo-koen-7B-V1.1",
    "datasets": [
      "squarelike/sharegpt_deepl_ko_translation"
    ],
    "language": [
      "en",
      "ko"
    ],
    "library_name": "transformers",
    "license": "apache-2.0",
    "quantized_by": "mradermacher",
    "frontmatter": {
      "base_model": "squarelike/Gugugo-koen-7B-V1.1",
      "datasets": [
        "squarelike/sharegpt_deepl_ko_translation"
      ],
      "language": [
        "en",
        "ko"
      ],
      "library_name": "transformers",
      "license": "apache-2.0",
      "quantized_by": "mradermacher"
    },
    "hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
    "summary": "## About      weighted/imatrix quants of https://huggingface.co/squarelike/Gugugo-koen-7B-V1.1  static quants are available at https://huggingface.co/mradermacher/Gugugo-koen-7B-V1.1-GGUF",
    "quick_links": [],
    "benchmark_table_html": "",
    "readme_markdown": "---\nbase_model: squarelike/Gugugo-koen-7B-V1.1\ndatasets:\n- squarelike/sharegpt_deepl_ko_translation\nlanguage:\n- en\n- ko\nlibrary_name: transformers\nlicense: apache-2.0\nquantized_by: mradermacher\n---\n## About\n\n<!-- ### quantize_version: 2 -->\n<!-- ### output_tensor_quantised: 1 -->\n<!-- ### convert_type: hf -->\n<!-- ### vocab_type:  -->\n<!-- ### tags: nicoboss -->\nweighted/imatrix quants of https://huggingface.co/squarelike/Gugugo-koen-7B-V1.1\n\n<!-- provided-files -->\nstatic quants are available at https://huggingface.co/mradermacher/Gugugo-koen-7B-V1.1-GGUF\n## Usage\n\nIf you are unsure how to use GGUF files, refer to one of [TheBloke's\nREADMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for\nmore details, including on how to concatenate multi-part files.\n\n## Provided Quants\n\n(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)\n\n| Link | Type | Size/GB | Notes |\n|:-----|:-----|--------:|:------|\n| [GGUF](https://huggingface.co/mradermacher/Gugugo-koen-7B-V1.1-i1-GGUF/resolve/main/Gugugo-koen-7B-V1.1.i1-IQ1_S.gguf) | i1-IQ1_S | 1.7 | for the desperate |\n| [GGUF](https://huggingface.co/mradermacher/Gugugo-koen-7B-V1.1-i1-GGUF/resolve/main/Gugugo-koen-7B-V1.1.i1-IQ1_M.gguf) | i1-IQ1_M | 1.8 | mostly desperate |\n| [GGUF](https://huggingface.co/mradermacher/Gugugo-koen-7B-V1.1-i1-GGUF/resolve/main/Gugugo-koen-7B-V1.1.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 2.0 |  |\n| [GGUF](https://huggingface.co/mradermacher/Gugugo-koen-7B-V1.1-i1-GGUF/resolve/main/Gugugo-koen-7B-V1.1.i1-IQ2_XS.gguf) | i1-IQ2_XS | 2.2 |  |\n| [GGUF](https://huggingface.co/mradermacher/Gugugo-koen-7B-V1.1-i1-GGUF/resolve/main/Gugugo-koen-7B-V1.1.i1-IQ2_S.gguf) | i1-IQ2_S | 2.4 |  |\n| [GGUF](https://huggingface.co/mradermacher/Gugugo-koen-7B-V1.1-i1-GGUF/resolve/main/Gugugo-koen-7B-V1.1.i1-Q2_K_S.gguf) | i1-Q2_K_S | 2.5 | very low quality |\n| [GGUF](https://huggingface.co/mradermacher/Gugugo-koen-7B-V1.1-i1-GGUF/resolve/main/Gugugo-koen-7B-V1.1.i1-IQ2_M.gguf) | i1-IQ2_M | 2.5 |  |\n| [GGUF](https://huggingface.co/mradermacher/Gugugo-koen-7B-V1.1-i1-GGUF/resolve/main/Gugugo-koen-7B-V1.1.i1-Q2_K.gguf) | i1-Q2_K | 2.7 | IQ3_XXS probably better |\n| [GGUF](https://huggingface.co/mradermacher/Gugugo-koen-7B-V1.1-i1-GGUF/resolve/main/Gugugo-koen-7B-V1.1.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 2.8 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/Gugugo-koen-7B-V1.1-i1-GGUF/resolve/main/Gugugo-koen-7B-V1.1.i1-IQ3_XS.gguf) | i1-IQ3_XS | 3.0 |  |\n| [GGUF](https://huggingface.co/mradermacher/Gugugo-koen-7B-V1.1-i1-GGUF/resolve/main/Gugugo-koen-7B-V1.1.i1-IQ3_S.gguf) | i1-IQ3_S | 3.1 | beats Q3_K* |\n| [GGUF](https://huggingface.co/mradermacher/Gugugo-koen-7B-V1.1-i1-GGUF/resolve/main/Gugugo-koen-7B-V1.1.i1-Q3_K_S.gguf) | i1-Q3_K_S | 3.1 | IQ3_XS probably better |\n| [GGUF](https://huggingface.co/mradermacher/Gugugo-koen-7B-V1.1-i1-GGUF/resolve/main/Gugugo-koen-7B-V1.1.i1-IQ3_M.gguf) | i1-IQ3_M | 3.3 |  |\n| [GGUF](https://huggingface.co/mradermacher/Gugugo-koen-7B-V1.1-i1-GGUF/resolve/main/Gugugo-koen-7B-V1.1.i1-Q3_K_M.gguf) | i1-Q3_K_M | 3.5 | IQ3_S probably better |\n| [GGUF](https://huggingface.co/mradermacher/Gugugo-koen-7B-V1.1-i1-GGUF/resolve/main/Gugugo-koen-7B-V1.1.i1-Q3_K_L.gguf) | i1-Q3_K_L | 3.8 | IQ3_M probably better |\n| [GGUF](https://huggingface.co/mradermacher/Gugugo-koen-7B-V1.1-i1-GGUF/resolve/main/Gugugo-koen-7B-V1.1.i1-IQ4_XS.gguf) | i1-IQ4_XS | 3.8 |  |\n| [GGUF](https://huggingface.co/mradermacher/Gugugo-koen-7B-V1.1-i1-GGUF/resolve/main/Gugugo-koen-7B-V1.1.i1-Q4_0_4_4.gguf) | i1-Q4_0_4_4 | 4.0 | fast on arm, low quality |\n| [GGUF](https://huggingface.co/mradermacher/Gugugo-koen-7B-V1.1-i1-GGUF/resolve/main/Gugugo-koen-7B-V1.1.i1-Q4_0_4_8.gguf) | i1-Q4_0_4_8 | 4.0 | fast on arm+i8mm, low quality |\n| [GGUF](https://huggingface.co/mradermacher/Gugugo-koen-7B-V1.1-i1-GGUF/resolve/main/Gugugo-koen-7B-V1.1.i1-Q4_0_8_8.gguf) | i1-Q4_0_8_8 | 4.0 | fast on arm+sve, low quality |\n| [GGUF](https://huggingface.co/mradermacher/Gugugo-koen-7B-V1.1-i1-GGUF/resolve/main/Gugugo-koen-7B-V1.1.i1-Q4_0.gguf) | i1-Q4_0 | 4.0 | fast, low quality |\n| [GGUF](https://huggingface.co/mradermacher/Gugugo-koen-7B-V1.1-i1-GGUF/resolve/main/Gugugo-koen-7B-V1.1.i1-Q4_K_S.gguf) | i1-Q4_K_S | 4.0 | optimal size/speed/quality |\n| [GGUF](https://huggingface.co/mradermacher/Gugugo-koen-7B-V1.1-i1-GGUF/resolve/main/Gugugo-koen-7B-V1.1.i1-Q4_K_M.gguf) | i1-Q4_K_M | 4.3 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/Gugugo-koen-7B-V1.1-i1-GGUF/resolve/main/Gugugo-koen-7B-V1.1.i1-Q5_K_S.gguf) | i1-Q5_K_S | 4.8 |  |\n| [GGUF](https://huggingface.co/mradermacher/Gugugo-koen-7B-V1.1-i1-GGUF/resolve/main/Gugugo-koen-7B-V1.1.i1-Q5_K_M.gguf) | i1-Q5_K_M | 5.0 |  |\n| [GGUF](https://huggingface.co/mradermacher/Gugugo-koen-7B-V1.1-i1-GGUF/resolve/main/Gugugo-koen-7B-V1.1.i1-Q6_K.gguf) | i1-Q6_K | 5.7 | practically like static Q6_K |\n\nHere is a handy graph by ikawrakow comparing some lower-quality quant\ntypes (lower is better):\n\n![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png)\n\nAnd here are Artefact2's thoughts on the matter:\nhttps://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9\n\n## FAQ / Model Request\n\nSee https://huggingface.co/mradermacher/model_requests for some answers to\nquestions you might have and/or if you want some other model quantized.\n\n## Thanks\n\nI thank my company, [nethype GmbH](https://www.nethype.de/), for letting\nme use its servers and providing upgrades to my workstation to enable\nthis work in my free time. Additional thanks to [@nicoboss](https://huggingface.co/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.\n\n<!-- end -->\n",
    "related_quantizations": []
  },
  "tags": [
    "transformers",
    "gguf",
    "en",
    "ko",
    "dataset:squarelike/sharegpt_deepl_ko_translation",
    "base_model:squarelike/Gugugo-koen-7B-V1.1",
    "base_model:quantized:squarelike/Gugugo-koen-7B-V1.1",
    "license:apache-2.0",
    "endpoints_compatible",
    "region:us",
    "imatrix"
  ],
  "likes": 0,
  "downloads": 115,
  "gated": false,
  "private": false,
  "last_modified": "2024-12-08T00:20:25.000Z",
  "created_at": "2024-12-07T22:05:29.000Z",
  "pipeline_tag": "",
  "library_name": "transformers"
}
Source payload excerpt (from Hugging Face API)
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  "createdAt": "2024-12-07T22:05:29.000Z",
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