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Model Intelligence Sheet

mradermacher/insllm-i1-gguf overview

About weighted/imatrix quants of https://huggingface.co/FrankRin/InsLLM static quants are available at https://huggingface.co/mradermacher/InsLLM-GGUF

transformersggufzhdataset:FrankRin/Insur-QAbase_model:FrankRin/InsLLMbase_model:quantized:FrankRin/InsLLMlicense:apache-2.0endpoints_compatibleregion:usimatrixconversational
mradermacher/insllm-i1-gguf visual
Downloads
655
Likes
0
Pipeline
Library
transformers
Visibility
Public
Access
Open

Repository Files & Downloads

24 files detected
Direct downloads for all repository files
FileTypeQuantizationSizeLink
InsLLM.i1-IQ1_M.gguf GGUF IQ1_M 4.36 GB Download
InsLLM.i1-IQ1_S.gguf GGUF IQ1_S 4.19 GB Download
InsLLM.i1-IQ2_M.gguf GGUF IQ2_M 5.43 GB Download
InsLLM.i1-IQ2_S.gguf GGUF IQ2_S 5.20 GB Download
InsLLM.i1-IQ2_XS.gguf GGUF IQ2_XS 4.89 GB Download
InsLLM.i1-IQ2_XXS.gguf GGUF IQ2_XXS 4.64 GB Download
InsLLM.i1-IQ3_M.gguf GGUF IQ3_M 6.61 GB Download
InsLLM.i1-IQ3_S.gguf GGUF IQ3_S 6.31 GB Download
InsLLM.i1-IQ3_XS.gguf GGUF IQ3_XS 6.03 GB Download
InsLLM.i1-IQ3_XXS.gguf GGUF IQ3_XXS 5.71 GB Download
InsLLM.i1-IQ4_NL.gguf GGUF IQ4_NL 7.62 GB Download
InsLLM.i1-IQ4_XS.gguf GGUF IQ4_XS 7.31 GB Download
InsLLM.i1-Q2_K.gguf GGUF Q2_K 5.51 GB Download
InsLLM.i1-Q2_K_S.gguf GGUF Q2_K_S 5.35 GB Download
InsLLM.i1-Q3_K_L.gguf GGUF Q3_K_L 7.30 GB Download
InsLLM.i1-Q3_K_M.gguf GGUF Q3_K_M 6.91 GB Download
InsLLM.i1-Q3_K_S.gguf GGUF Q3_K_S 6.31 GB Download
InsLLM.i1-Q4_0.gguf GGUF 7.64 GB Download
InsLLM.i1-Q4_1.gguf GGUF 8.40 GB Download
InsLLM.i1-Q4_K_M.gguf GGUF Q4_K_M 8.56 GB Download
InsLLM.i1-Q4_K_S.gguf GGUF Q4_K_S 7.98 GB Download
InsLLM.i1-Q5_K_M.gguf GGUF Q5_K_M 9.81 GB Download
InsLLM.i1-Q5_K_S.gguf GGUF Q5_K_S 9.34 GB Download
InsLLM.i1-Q6_K.gguf GGUF Q6_K 11.46 GB Download

Model Details Live

Model Slug
mradermacher/insllm-i1-gguf
Author
mradermacher
Pipeline Task
Library
transformers
Created
2025-04-25
Last Modified
2025-04-25
Gated
No
Private
No
HF SHA
1d45faaea9328e33e98020634bd99fbd3e7cdd00
License
apache-2.0
Language
zh
Base Model
FrankRin/InsLLM

Metadata Inspector

Normalized metadata (stored in metadata_json)
{
  "metadata": {},
  "card_data": {
    "base_model": "FrankRin/InsLLM",
    "datasets": [
      "FrankRin/Insur-QA"
    ],
    "language": [
      "zh"
    ],
    "library_name": "transformers",
    "license": "apache-2.0",
    "quantized_by": "mradermacher",
    "frontmatter": {
      "base_model": "FrankRin/InsLLM",
      "datasets": [
        "FrankRin/Insur-QA"
      ],
      "language": [
        "zh"
      ],
      "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/FrankRin/InsLLM  static quants are available at https://huggingface.co/mradermacher/InsLLM-GGUF",
    "quick_links": [],
    "benchmark_table_html": "",
    "readme_markdown": "---\nbase_model: FrankRin/InsLLM\ndatasets:\n- FrankRin/Insur-QA\nlanguage:\n- zh\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/FrankRin/InsLLM\n\n<!-- provided-files -->\nstatic quants are available at https://huggingface.co/mradermacher/InsLLM-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/InsLLM-i1-GGUF/resolve/main/InsLLM.i1-IQ1_S.gguf) | i1-IQ1_S | 4.6 | for the desperate |\n| [GGUF](https://huggingface.co/mradermacher/InsLLM-i1-GGUF/resolve/main/InsLLM.i1-IQ1_M.gguf) | i1-IQ1_M | 4.8 | mostly desperate |\n| [GGUF](https://huggingface.co/mradermacher/InsLLM-i1-GGUF/resolve/main/InsLLM.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 5.1 |  |\n| [GGUF](https://huggingface.co/mradermacher/InsLLM-i1-GGUF/resolve/main/InsLLM.i1-IQ2_XS.gguf) | i1-IQ2_XS | 5.4 |  |\n| [GGUF](https://huggingface.co/mradermacher/InsLLM-i1-GGUF/resolve/main/InsLLM.i1-IQ2_S.gguf) | i1-IQ2_S | 5.7 |  |\n| [GGUF](https://huggingface.co/mradermacher/InsLLM-i1-GGUF/resolve/main/InsLLM.i1-Q2_K_S.gguf) | i1-Q2_K_S | 5.8 | very low quality |\n| [GGUF](https://huggingface.co/mradermacher/InsLLM-i1-GGUF/resolve/main/InsLLM.i1-IQ2_M.gguf) | i1-IQ2_M | 5.9 |  |\n| [GGUF](https://huggingface.co/mradermacher/InsLLM-i1-GGUF/resolve/main/InsLLM.i1-Q2_K.gguf) | i1-Q2_K | 6.0 | IQ3_XXS probably better |\n| [GGUF](https://huggingface.co/mradermacher/InsLLM-i1-GGUF/resolve/main/InsLLM.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 6.2 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/InsLLM-i1-GGUF/resolve/main/InsLLM.i1-IQ3_XS.gguf) | i1-IQ3_XS | 6.6 |  |\n| [GGUF](https://huggingface.co/mradermacher/InsLLM-i1-GGUF/resolve/main/InsLLM.i1-IQ3_S.gguf) | i1-IQ3_S | 6.9 | beats Q3_K* |\n| [GGUF](https://huggingface.co/mradermacher/InsLLM-i1-GGUF/resolve/main/InsLLM.i1-Q3_K_S.gguf) | i1-Q3_K_S | 6.9 | IQ3_XS probably better |\n| [GGUF](https://huggingface.co/mradermacher/InsLLM-i1-GGUF/resolve/main/InsLLM.i1-IQ3_M.gguf) | i1-IQ3_M | 7.2 |  |\n| [GGUF](https://huggingface.co/mradermacher/InsLLM-i1-GGUF/resolve/main/InsLLM.i1-Q3_K_M.gguf) | i1-Q3_K_M | 7.5 | IQ3_S probably better |\n| [GGUF](https://huggingface.co/mradermacher/InsLLM-i1-GGUF/resolve/main/InsLLM.i1-Q3_K_L.gguf) | i1-Q3_K_L | 7.9 | IQ3_M probably better |\n| [GGUF](https://huggingface.co/mradermacher/InsLLM-i1-GGUF/resolve/main/InsLLM.i1-IQ4_XS.gguf) | i1-IQ4_XS | 7.9 |  |\n| [GGUF](https://huggingface.co/mradermacher/InsLLM-i1-GGUF/resolve/main/InsLLM.i1-IQ4_NL.gguf) | i1-IQ4_NL | 8.3 | prefer IQ4_XS |\n| [GGUF](https://huggingface.co/mradermacher/InsLLM-i1-GGUF/resolve/main/InsLLM.i1-Q4_0.gguf) | i1-Q4_0 | 8.3 | fast, low quality |\n| [GGUF](https://huggingface.co/mradermacher/InsLLM-i1-GGUF/resolve/main/InsLLM.i1-Q4_K_S.gguf) | i1-Q4_K_S | 8.7 | optimal size/speed/quality |\n| [GGUF](https://huggingface.co/mradermacher/InsLLM-i1-GGUF/resolve/main/InsLLM.i1-Q4_1.gguf) | i1-Q4_1 | 9.1 |  |\n| [GGUF](https://huggingface.co/mradermacher/InsLLM-i1-GGUF/resolve/main/InsLLM.i1-Q4_K_M.gguf) | i1-Q4_K_M | 9.3 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/InsLLM-i1-GGUF/resolve/main/InsLLM.i1-Q5_K_S.gguf) | i1-Q5_K_S | 10.1 |  |\n| [GGUF](https://huggingface.co/mradermacher/InsLLM-i1-GGUF/resolve/main/InsLLM.i1-Q5_K_M.gguf) | i1-Q5_K_M | 10.6 |  |\n| [GGUF](https://huggingface.co/mradermacher/InsLLM-i1-GGUF/resolve/main/InsLLM.i1-Q6_K.gguf) | i1-Q6_K | 12.4 | 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",
    "zh",
    "dataset:FrankRin/Insur-QA",
    "base_model:FrankRin/InsLLM",
    "base_model:quantized:FrankRin/InsLLM",
    "license:apache-2.0",
    "endpoints_compatible",
    "region:us",
    "imatrix",
    "conversational"
  ],
  "likes": 0,
  "downloads": 655,
  "gated": false,
  "private": false,
  "last_modified": "2025-04-25T22:00:07.000Z",
  "created_at": "2025-04-25T19:52:55.000Z",
  "pipeline_tag": "",
  "library_name": "transformers"
}
Source payload excerpt (from Hugging Face API)
{
  "_id": "680be8178af7cf221be939ad",
  "id": "mradermacher/InsLLM-i1-GGUF",
  "modelId": "mradermacher/InsLLM-i1-GGUF",
  "sha": "1d45faaea9328e33e98020634bd99fbd3e7cdd00",
  "createdAt": "2025-04-25T19:52:55.000Z",
  "lastModified": "2025-04-25T22:00:07.000Z",
  "author": "mradermacher",
  "downloads": 655,
  "likes": 0,
  "gated": false,
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  "pipeline_tag": "",
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  "siblings_count": 27
}