mradermacher/bigqwen2.5-125b-instruct-i1-gguf overview

{
  "metadata": {},
  "card_data": {
    "base_model": "mlabonne/BigQwen2.5-125B-Instruct",
    "language": [
      "zho",
      "eng",
      "fra",
      "spa",
      "por",
      "deu",
      "ita",
      "rus",
      "jpn",
      "kor",
      "vie",
      "tha",
      "ara"
    ],
    "library_name": "transformers",
    "license": "other",
    "license_link": "https://huggingface.co/Qwen/Qwen2-72B-Instruct/blob/main/LICENSE",
    "license_name": "tongyi-qianwen",
    "quantized_by": "mradermacher",
    "tags": [
      "mergekit",
      "merge",
      "lazymergekit"
    ],
    "frontmatter": {
      "base_model": "mlabonne/BigQwen2.5-125B-Instruct",
      "language": [
        "zho",
        "eng",
        "fra",
        "spa",
        "por",
        "deu",
        "ita",
        "rus",
        "jpn",
        "kor",
        "vie",
        "tha",
        "ara"
      ],
      "library_name": "transformers",
      "license": "other",
      "license_link": "https://huggingface.co/Qwen/Qwen2-72B-Instruct/blob/main/LICENSE",
      "license_name": "tongyi-qianwen",
      "quantized_by": "mradermacher",
      "tags": [
        "mergekit",
        "merge",
        "lazymergekit"
      ]
    },
    "hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
    "summary": "## About      weighted/imatrix quants of https://huggingface.co/mlabonne/BigQwen2.5-125B-Instruct  static quants are available at https://huggingface.co/mradermacher/BigQwen2.5-125B-Instruct-GGUF",
    "quick_links": [],
    "benchmark_table_html": "",
    "readme_markdown": "---\nbase_model: mlabonne/BigQwen2.5-125B-Instruct\nlanguage:\n- zho\n- eng\n- fra\n- spa\n- por\n- deu\n- ita\n- rus\n- jpn\n- kor\n- vie\n- tha\n- ara\nlibrary_name: transformers\nlicense: other\nlicense_link: https://huggingface.co/Qwen/Qwen2-72B-Instruct/blob/main/LICENSE\nlicense_name: tongyi-qianwen\nquantized_by: mradermacher\ntags:\n- mergekit\n- merge\n- lazymergekit\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/mlabonne/BigQwen2.5-125B-Instruct\n\n<!-- provided-files -->\nstatic quants are available at https://huggingface.co/mradermacher/BigQwen2.5-125B-Instruct-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/BigQwen2.5-125B-Instruct-i1-GGUF/resolve/main/BigQwen2.5-125B-Instruct.i1-IQ1_S.gguf) | i1-IQ1_S | 38.9 | for the desperate |\n| [GGUF](https://huggingface.co/mradermacher/BigQwen2.5-125B-Instruct-i1-GGUF/resolve/main/BigQwen2.5-125B-Instruct.i1-IQ1_M.gguf) | i1-IQ1_M | 40.7 | mostly desperate |\n| [GGUF](https://huggingface.co/mradermacher/BigQwen2.5-125B-Instruct-i1-GGUF/resolve/main/BigQwen2.5-125B-Instruct.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 43.8 |  |\n| [GGUF](https://huggingface.co/mradermacher/BigQwen2.5-125B-Instruct-i1-GGUF/resolve/main/BigQwen2.5-125B-Instruct.i1-IQ2_XS.gguf) | i1-IQ2_XS | 46.5 |  |\n| [GGUF](https://huggingface.co/mradermacher/BigQwen2.5-125B-Instruct-i1-GGUF/resolve/main/BigQwen2.5-125B-Instruct.i1-IQ2_S.gguf) | i1-IQ2_S | 47.9 |  |\n| [PART 1](https://huggingface.co/mradermacher/BigQwen2.5-125B-Instruct-i1-GGUF/resolve/main/BigQwen2.5-125B-Instruct.i1-IQ2_M.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/BigQwen2.5-125B-Instruct-i1-GGUF/resolve/main/BigQwen2.5-125B-Instruct.i1-IQ2_M.gguf.part2of2) | i1-IQ2_M | 50.4 |  |\n| [PART 1](https://huggingface.co/mradermacher/BigQwen2.5-125B-Instruct-i1-GGUF/resolve/main/BigQwen2.5-125B-Instruct.i1-Q2_K.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/BigQwen2.5-125B-Instruct-i1-GGUF/resolve/main/BigQwen2.5-125B-Instruct.i1-Q2_K.gguf.part2of2) | i1-Q2_K | 51.0 | IQ3_XXS probably better |\n| [PART 1](https://huggingface.co/mradermacher/BigQwen2.5-125B-Instruct-i1-GGUF/resolve/main/BigQwen2.5-125B-Instruct.i1-IQ3_XXS.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/BigQwen2.5-125B-Instruct-i1-GGUF/resolve/main/BigQwen2.5-125B-Instruct.i1-IQ3_XXS.gguf.part2of2) | i1-IQ3_XXS | 54.6 | lower quality |\n| [PART 1](https://huggingface.co/mradermacher/BigQwen2.5-125B-Instruct-i1-GGUF/resolve/main/BigQwen2.5-125B-Instruct.i1-IQ3_XS.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/BigQwen2.5-125B-Instruct-i1-GGUF/resolve/main/BigQwen2.5-125B-Instruct.i1-IQ3_XS.gguf.part2of2) | i1-IQ3_XS | 56.3 |  |\n| [PART 1](https://huggingface.co/mradermacher/BigQwen2.5-125B-Instruct-i1-GGUF/resolve/main/BigQwen2.5-125B-Instruct.i1-Q3_K_S.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/BigQwen2.5-125B-Instruct-i1-GGUF/resolve/main/BigQwen2.5-125B-Instruct.i1-Q3_K_S.gguf.part2of2) | i1-Q3_K_S | 59.0 | IQ3_XS probably better |\n| [PART 1](https://huggingface.co/mradermacher/BigQwen2.5-125B-Instruct-i1-GGUF/resolve/main/BigQwen2.5-125B-Instruct.i1-IQ3_S.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/BigQwen2.5-125B-Instruct-i1-GGUF/resolve/main/BigQwen2.5-125B-Instruct.i1-IQ3_S.gguf.part2of2) | i1-IQ3_S | 59.1 | beats Q3_K* |\n| [PART 1](https://huggingface.co/mradermacher/BigQwen2.5-125B-Instruct-i1-GGUF/resolve/main/BigQwen2.5-125B-Instruct.i1-IQ3_M.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/BigQwen2.5-125B-Instruct-i1-GGUF/resolve/main/BigQwen2.5-125B-Instruct.i1-IQ3_M.gguf.part2of2) | i1-IQ3_M | 60.9 |  |\n| [PART 1](https://huggingface.co/mradermacher/BigQwen2.5-125B-Instruct-i1-GGUF/resolve/main/BigQwen2.5-125B-Instruct.i1-Q3_K_M.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/BigQwen2.5-125B-Instruct-i1-GGUF/resolve/main/BigQwen2.5-125B-Instruct.i1-Q3_K_M.gguf.part2of2) | i1-Q3_K_M | 64.7 | IQ3_S probably better |\n| [PART 1](https://huggingface.co/mradermacher/BigQwen2.5-125B-Instruct-i1-GGUF/resolve/main/BigQwen2.5-125B-Instruct.i1-Q3_K_L.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/BigQwen2.5-125B-Instruct-i1-GGUF/resolve/main/BigQwen2.5-125B-Instruct.i1-Q3_K_L.gguf.part2of2) | i1-Q3_K_L | 68.1 | IQ3_M probably better |\n| [PART 1](https://huggingface.co/mradermacher/BigQwen2.5-125B-Instruct-i1-GGUF/resolve/main/BigQwen2.5-125B-Instruct.i1-IQ4_XS.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/BigQwen2.5-125B-Instruct-i1-GGUF/resolve/main/BigQwen2.5-125B-Instruct.i1-IQ4_XS.gguf.part2of2) | i1-IQ4_XS | 68.3 |  |\n| [PART 1](https://huggingface.co/mradermacher/BigQwen2.5-125B-Instruct-i1-GGUF/resolve/main/BigQwen2.5-125B-Instruct.i1-Q4_0.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/BigQwen2.5-125B-Instruct-i1-GGUF/resolve/main/BigQwen2.5-125B-Instruct.i1-Q4_0.gguf.part2of2) | i1-Q4_0 | 71.2 | fast, low quality |\n| [PART 1](https://huggingface.co/mradermacher/BigQwen2.5-125B-Instruct-i1-GGUF/resolve/main/BigQwen2.5-125B-Instruct.i1-Q4_K_S.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/BigQwen2.5-125B-Instruct-i1-GGUF/resolve/main/BigQwen2.5-125B-Instruct.i1-Q4_K_S.gguf.part2of2) | i1-Q4_K_S | 75.5 | optimal size/speed/quality |\n| [PART 1](https://huggingface.co/mradermacher/BigQwen2.5-125B-Instruct-i1-GGUF/resolve/main/BigQwen2.5-125B-Instruct.i1-Q4_K_M.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/BigQwen2.5-125B-Instruct-i1-GGUF/resolve/main/BigQwen2.5-125B-Instruct.i1-Q4_K_M.gguf.part2of2) | i1-Q4_K_M | 81.7 | fast, recommended |\n| [PART 1](https://huggingface.co/mradermacher/BigQwen2.5-125B-Instruct-i1-GGUF/resolve/main/BigQwen2.5-125B-Instruct.i1-Q5_K_S.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/BigQwen2.5-125B-Instruct-i1-GGUF/resolve/main/BigQwen2.5-125B-Instruct.i1-Q5_K_S.gguf.part2of2) | i1-Q5_K_S | 88.6 |  |\n| [PART 1](https://huggingface.co/mradermacher/BigQwen2.5-125B-Instruct-i1-GGUF/resolve/main/BigQwen2.5-125B-Instruct.i1-Q5_K_M.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/BigQwen2.5-125B-Instruct-i1-GGUF/resolve/main/BigQwen2.5-125B-Instruct.i1-Q5_K_M.gguf.part2of2) | i1-Q5_K_M | 94.0 |  |\n| [PART 1](https://huggingface.co/mradermacher/BigQwen2.5-125B-Instruct-i1-GGUF/resolve/main/BigQwen2.5-125B-Instruct.i1-Q6_K.gguf.part1of3) [PART 2](https://huggingface.co/mradermacher/BigQwen2.5-125B-Instruct-i1-GGUF/resolve/main/BigQwen2.5-125B-Instruct.i1-Q6_K.gguf.part2of3) [PART 3](https://huggingface.co/mradermacher/BigQwen2.5-125B-Instruct-i1-GGUF/resolve/main/BigQwen2.5-125B-Instruct.i1-Q6_K.gguf.part3of3) | i1-Q6_K | 111.2 | 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",
    "mergekit",
    "merge",
    "lazymergekit",
    "zho",
    "eng",
    "fra",
    "spa",
    "por",
    "deu",
    "ita",
    "rus",
    "jpn",
    "kor",
    "vie",
    "tha",
    "ara",
    "base_model:mlabonne/BigQwen2.5-125B-Instruct",
    "base_model:quantized:mlabonne/BigQwen2.5-125B-Instruct",
    "license:other",
    "endpoints_compatible",
    "region:us",
    "imatrix",
    "conversational"
  ],
  "likes": 0,
  "downloads": 357,
  "gated": false,
  "private": false,
  "last_modified": "2025-04-30T05:16:03.000Z",
  "created_at": "2024-09-24T12:53:44.000Z",
  "pipeline_tag": "",
  "library_name": "transformers"
}

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