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mradermacher/internlm2-math-base-7b-gguf Q5_K_S 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.

Model Intelligence Sheet

mradermacher/internlm2-math-base-7b-gguf overview

About static quants of https://huggingface.co/internlm/internlm2-math-base-7b weighted/imatrix quants are available at https://huggingface.co/mradermacher/internlm2-math-base-7b-i1-GGUF

transformersggufmathenzhbase_model:internlm/internlm2-math-base-7bbase_model:quantized:internlm/internlm2-math-base-7blicense:otherendpoints_compatibleregion:usconversational
mradermacher/internlm2-math-base-7b-gguf visual
Downloads
101
Likes
0
Pipeline
Library
transformers
Visibility
Public
Access
Open

Repository Files & Downloads

15 files detected
Direct downloads for all repository files
FileTypeQuantizationSizeLink
internlm2-math-base-7b.IQ3_M.gguf GGUF IQ3_M 3.35 GB Download
internlm2-math-base-7b.IQ3_S.gguf GGUF IQ3_S 3.25 GB Download
internlm2-math-base-7b.IQ3_XS.gguf GGUF IQ3_XS 3.10 GB Download
internlm2-math-base-7b.IQ4_XS.gguf GGUF IQ4_XS 3.99 GB Download
internlm2-math-base-7b.Q2_K.gguf GGUF Q2_K 2.80 GB Download
internlm2-math-base-7b.Q3_K_L.gguf GGUF Q3_K_L 3.85 GB Download
internlm2-math-base-7b.Q3_K_M.gguf GGUF Q3_K_M 3.57 GB Download
internlm2-math-base-7b.Q3_K_S.gguf GGUF Q3_K_S 3.24 GB Download
internlm2-math-base-7b.Q4_K_M.gguf GGUF Q4_K_M 4.39 GB Download
internlm2-math-base-7b.Q4_K_S.gguf GGUF Q4_K_S 4.18 GB Download
internlm2-math-base-7b.Q5_K_M.gguf GGUF Q5_K_M 5.13 GB Download
internlm2-math-base-7b.Q5_K_S.gguf GGUF Q5_K_S 5.00 GB Download
internlm2-math-base-7b.Q6_K.gguf GGUF Q6_K 5.91 GB Download
internlm2-math-base-7b.Q8_0.gguf GGUF 7.66 GB Download
internlm2-math-base-7b.f16.gguf GGUF F16 14.42 GB Download

Model Details Live

Model Slug
mradermacher/internlm2-math-base-7b-gguf
Author
mradermacher
Pipeline Task
Library
transformers
Created
2024-08-21
Last Modified
2024-08-21
Gated
No
Private
No
HF SHA
6a1c3293896328f3b3c2334210fc5b8cd63a36e7
License
other
Language
en, zh
Base Model
internlm/internlm2-math-base-7b

Metadata Inspector

Normalized metadata (stored in metadata_json)
{
  "metadata": {},
  "card_data": {
    "base_model": "internlm/internlm2-math-base-7b",
    "language": [
      "en",
      "zh"
    ],
    "library_name": "transformers",
    "license": "other",
    "quantized_by": "mradermacher",
    "tags": [
      "math"
    ],
    "frontmatter": {
      "base_model": "internlm/internlm2-math-base-7b",
      "language": [
        "en",
        "zh"
      ],
      "library_name": "transformers",
      "license": "other",
      "quantized_by": "mradermacher",
      "tags": [
        "math"
      ]
    },
    "hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
    "summary": "## About      static quants of https://huggingface.co/internlm/internlm2-math-base-7b  weighted/imatrix quants are available at https://huggingface.co/mradermacher/internlm2-math-base-7b-i1-GGUF",
    "quick_links": [],
    "benchmark_table_html": "",
    "readme_markdown": "---\nbase_model: internlm/internlm2-math-base-7b\nlanguage:\n- en\n- zh\nlibrary_name: transformers\nlicense: other\nquantized_by: mradermacher\ntags:\n- math\n---\n## About\n\n<!-- ### quantize_version: 2 -->\n<!-- ### output_tensor_quantised: 1 -->\n<!-- ### convert_type: hf -->\n<!-- ### vocab_type:  -->\n<!-- ### tags:  -->\nstatic quants of https://huggingface.co/internlm/internlm2-math-base-7b\n\n<!-- provided-files -->\nweighted/imatrix quants are available at https://huggingface.co/mradermacher/internlm2-math-base-7b-i1-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/internlm2-math-base-7b-GGUF/resolve/main/internlm2-math-base-7b.Q2_K.gguf) | Q2_K | 3.1 |  |\n| [GGUF](https://huggingface.co/mradermacher/internlm2-math-base-7b-GGUF/resolve/main/internlm2-math-base-7b.IQ3_XS.gguf) | IQ3_XS | 3.4 |  |\n| [GGUF](https://huggingface.co/mradermacher/internlm2-math-base-7b-GGUF/resolve/main/internlm2-math-base-7b.Q3_K_S.gguf) | Q3_K_S | 3.6 |  |\n| [GGUF](https://huggingface.co/mradermacher/internlm2-math-base-7b-GGUF/resolve/main/internlm2-math-base-7b.IQ3_S.gguf) | IQ3_S | 3.6 | beats Q3_K* |\n| [GGUF](https://huggingface.co/mradermacher/internlm2-math-base-7b-GGUF/resolve/main/internlm2-math-base-7b.IQ3_M.gguf) | IQ3_M | 3.7 |  |\n| [GGUF](https://huggingface.co/mradermacher/internlm2-math-base-7b-GGUF/resolve/main/internlm2-math-base-7b.Q3_K_M.gguf) | Q3_K_M | 3.9 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/internlm2-math-base-7b-GGUF/resolve/main/internlm2-math-base-7b.Q3_K_L.gguf) | Q3_K_L | 4.2 |  |\n| [GGUF](https://huggingface.co/mradermacher/internlm2-math-base-7b-GGUF/resolve/main/internlm2-math-base-7b.IQ4_XS.gguf) | IQ4_XS | 4.4 |  |\n| [GGUF](https://huggingface.co/mradermacher/internlm2-math-base-7b-GGUF/resolve/main/internlm2-math-base-7b.Q4_K_S.gguf) | Q4_K_S | 4.6 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/internlm2-math-base-7b-GGUF/resolve/main/internlm2-math-base-7b.Q4_K_M.gguf) | Q4_K_M | 4.8 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/internlm2-math-base-7b-GGUF/resolve/main/internlm2-math-base-7b.Q5_K_S.gguf) | Q5_K_S | 5.5 |  |\n| [GGUF](https://huggingface.co/mradermacher/internlm2-math-base-7b-GGUF/resolve/main/internlm2-math-base-7b.Q5_K_M.gguf) | Q5_K_M | 5.6 |  |\n| [GGUF](https://huggingface.co/mradermacher/internlm2-math-base-7b-GGUF/resolve/main/internlm2-math-base-7b.Q6_K.gguf) | Q6_K | 6.5 | very good quality |\n| [GGUF](https://huggingface.co/mradermacher/internlm2-math-base-7b-GGUF/resolve/main/internlm2-math-base-7b.Q8_0.gguf) | Q8_0 | 8.3 | fast, best quality |\n| [GGUF](https://huggingface.co/mradermacher/internlm2-math-base-7b-GGUF/resolve/main/internlm2-math-base-7b.f16.gguf) | f16 | 15.6 | 16 bpw, overkill |\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.\n\n<!-- end -->\n",
    "related_quantizations": []
  },
  "tags": [
    "transformers",
    "gguf",
    "math",
    "en",
    "zh",
    "base_model:internlm/internlm2-math-base-7b",
    "base_model:quantized:internlm/internlm2-math-base-7b",
    "license:other",
    "endpoints_compatible",
    "region:us",
    "conversational"
  ],
  "likes": 0,
  "downloads": 101,
  "gated": false,
  "private": false,
  "last_modified": "2024-08-21T10:50:24.000Z",
  "created_at": "2024-08-21T08:48:30.000Z",
  "pipeline_tag": "",
  "library_name": "transformers"
}
Source payload excerpt (from Hugging Face API)
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  "createdAt": "2024-08-21T08:48:30.000Z",
  "lastModified": "2024-08-21T10:50:24.000Z",
  "author": "mradermacher",
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