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mradermacher/mini-cogito-r1-i1-gguf overview

About weighted/imatrix quants of https://huggingface.co/Daemontatox/mini-Cogito-R1 static quants are available at https://huggingface.co/mradermacher/mini-Cogito-R1-GGUF

transformersgguftext-generation-inferenceunslothqwen2trlreasoningfinetuneedge-deviceresearchendataset:bespokelabs/Bespoke-Stratos-17kdataset:simplescaling/s1Kdataset:cognitivecomputations/dolphin-r1dataset:openai/gsm8kdataset:PrimeIntellect/NuminaMath-QwQ-CoT-5Mlicense:apache-2.0endpoints_compatibleregion:usimatrixconversational
mradermacher/mini-cogito-r1-i1-gguf visual
Downloads
392
Likes
0
Pipeline
Library
transformers
Visibility
Public
Access
Open

Repository Files & Downloads

24 files detected
Direct downloads for all repository files
FileTypeQuantizationSizeLink
mini-Cogito-R1.i1-IQ1_M.gguf GGUF IQ1_M 515.97 MB Download
mini-Cogito-R1.i1-IQ1_S.gguf GGUF IQ1_S 489.34 MB Download
mini-Cogito-R1.i1-IQ2_M.gguf GGUF IQ2_M 668.84 MB Download
mini-Cogito-R1.i1-IQ2_S.gguf GGUF IQ2_S 633.32 MB Download
mini-Cogito-R1.i1-IQ2_XS.gguf GGUF IQ2_XS 597.86 MB Download
mini-Cogito-R1.i1-IQ2_XXS.gguf GGUF IQ2_XXS 560.37 MB Download
mini-Cogito-R1.i1-IQ3_M.gguf GGUF IQ3_M 836.32 MB Download
mini-Cogito-R1.i1-IQ3_S.gguf GGUF IQ3_S 822.72 MB Download
mini-Cogito-R1.i1-IQ3_XS.gguf GGUF IQ3_XS 793.44 MB Download
mini-Cogito-R1.i1-IQ3_XXS.gguf GGUF IQ3_XXS 733.44 MB Download
mini-Cogito-R1.i1-IQ4_NL.gguf GGUF IQ4_NL 1018.15 MB Download
mini-Cogito-R1.i1-IQ4_XS.gguf GGUF IQ4_XS 972.47 MB Download
mini-Cogito-R1.i1-Q2_K.gguf GGUF Q2_K 718.00 MB Download
mini-Cogito-R1.i1-Q2_K_S.gguf GGUF Q2_K_S 683.51 MB Download
mini-Cogito-R1.i1-Q3_K_L.gguf GGUF Q3_K_L 935.02 MB Download
mini-Cogito-R1.i1-Q3_K_M.gguf GGUF Q3_K_M 881.63 MB Download
mini-Cogito-R1.i1-Q3_K_S.gguf GGUF Q3_K_S 821.33 MB Download
mini-Cogito-R1.i1-Q4_0.gguf GGUF 1019.30 MB Download
mini-Cogito-R1.i1-Q4_1.gguf GGUF 1.08 GB Download
mini-Cogito-R1.i1-Q4_K_M.gguf GGUF Q4_K_M 1.04 GB Download
mini-Cogito-R1.i1-Q4_K_S.gguf GGUF Q4_K_S 1021.95 MB Download
mini-Cogito-R1.i1-Q5_K_M.gguf GGUF Q5_K_M 1.20 GB Download
mini-Cogito-R1.i1-Q5_K_S.gguf GGUF Q5_K_S 1.17 GB Download
mini-Cogito-R1.i1-Q6_K.gguf GGUF Q6_K 1.36 GB Download

Model Details Live

Model Slug
mradermacher/mini-cogito-r1-i1-gguf
Author
mradermacher
Pipeline Task
Library
transformers
Created
2025-02-23
Last Modified
2025-02-23
Gated
No
Private
No
HF SHA
b2477722e6e892d3b113ea91e9cbc7c7f4811460
License
apache-2.0
Language
en
Base Model
Daemontatox/mini-Cogito-R1

Metadata Inspector

Normalized metadata (stored in metadata_json)
{
  "metadata": {},
  "card_data": {
    "base_model": "Daemontatox/mini-Cogito-R1",
    "datasets": [
      "bespokelabs/Bespoke-Stratos-17k",
      "simplescaling/s1K",
      "cognitivecomputations/dolphin-r1",
      "openai/gsm8k",
      "PrimeIntellect/NuminaMath-QwQ-CoT-5M"
    ],
    "language": [
      "en"
    ],
    "library_name": "transformers",
    "license": "apache-2.0",
    "quantized_by": "mradermacher",
    "tags": [
      "text-generation-inference",
      "transformers",
      "unsloth",
      "qwen2",
      "trl",
      "reasoning",
      "finetune",
      "edge-device",
      "research"
    ],
    "frontmatter": {
      "base_model": "Daemontatox/mini-Cogito-R1",
      "datasets": [
        "bespokelabs/Bespoke-Stratos-17k",
        "simplescaling/s1K",
        "cognitivecomputations/dolphin-r1",
        "openai/gsm8k",
        "PrimeIntellect/NuminaMath-QwQ-CoT-5M"
      ],
      "language": [
        "en"
      ],
      "library_name": "transformers",
      "license": "apache-2.0",
      "quantized_by": "mradermacher",
      "tags": [
        "text-generation-inference",
        "transformers",
        "unsloth",
        "qwen2",
        "trl",
        "reasoning",
        "finetune",
        "edge-device",
        "research"
      ]
    },
    "hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
    "summary": "## About      weighted/imatrix quants of https://huggingface.co/Daemontatox/mini-Cogito-R1  static quants are available at https://huggingface.co/mradermacher/mini-Cogito-R1-GGUF",
    "quick_links": [],
    "benchmark_table_html": "",
    "readme_markdown": "---\nbase_model: Daemontatox/mini-Cogito-R1\ndatasets:\n- bespokelabs/Bespoke-Stratos-17k\n- simplescaling/s1K\n- cognitivecomputations/dolphin-r1\n- openai/gsm8k\n- PrimeIntellect/NuminaMath-QwQ-CoT-5M\nlanguage:\n- en\nlibrary_name: transformers\nlicense: apache-2.0\nquantized_by: mradermacher\ntags:\n- text-generation-inference\n- transformers\n- unsloth\n- qwen2\n- trl\n- reasoning\n- finetune\n- edge-device\n- research\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/Daemontatox/mini-Cogito-R1\n\n<!-- provided-files -->\nstatic quants are available at https://huggingface.co/mradermacher/mini-Cogito-R1-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/mini-Cogito-R1-i1-GGUF/resolve/main/mini-Cogito-R1.i1-IQ1_S.gguf) | i1-IQ1_S | 0.6 | for the desperate |\n| [GGUF](https://huggingface.co/mradermacher/mini-Cogito-R1-i1-GGUF/resolve/main/mini-Cogito-R1.i1-IQ1_M.gguf) | i1-IQ1_M | 0.6 | mostly desperate |\n| [GGUF](https://huggingface.co/mradermacher/mini-Cogito-R1-i1-GGUF/resolve/main/mini-Cogito-R1.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 0.7 |  |\n| [GGUF](https://huggingface.co/mradermacher/mini-Cogito-R1-i1-GGUF/resolve/main/mini-Cogito-R1.i1-IQ2_XS.gguf) | i1-IQ2_XS | 0.7 |  |\n| [GGUF](https://huggingface.co/mradermacher/mini-Cogito-R1-i1-GGUF/resolve/main/mini-Cogito-R1.i1-IQ2_S.gguf) | i1-IQ2_S | 0.8 |  |\n| [GGUF](https://huggingface.co/mradermacher/mini-Cogito-R1-i1-GGUF/resolve/main/mini-Cogito-R1.i1-IQ2_M.gguf) | i1-IQ2_M | 0.8 |  |\n| [GGUF](https://huggingface.co/mradermacher/mini-Cogito-R1-i1-GGUF/resolve/main/mini-Cogito-R1.i1-Q2_K_S.gguf) | i1-Q2_K_S | 0.8 | very low quality |\n| [GGUF](https://huggingface.co/mradermacher/mini-Cogito-R1-i1-GGUF/resolve/main/mini-Cogito-R1.i1-Q2_K.gguf) | i1-Q2_K | 0.9 | IQ3_XXS probably better |\n| [GGUF](https://huggingface.co/mradermacher/mini-Cogito-R1-i1-GGUF/resolve/main/mini-Cogito-R1.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 0.9 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/mini-Cogito-R1-i1-GGUF/resolve/main/mini-Cogito-R1.i1-IQ3_XS.gguf) | i1-IQ3_XS | 0.9 |  |\n| [GGUF](https://huggingface.co/mradermacher/mini-Cogito-R1-i1-GGUF/resolve/main/mini-Cogito-R1.i1-Q3_K_S.gguf) | i1-Q3_K_S | 1.0 | IQ3_XS probably better |\n| [GGUF](https://huggingface.co/mradermacher/mini-Cogito-R1-i1-GGUF/resolve/main/mini-Cogito-R1.i1-IQ3_S.gguf) | i1-IQ3_S | 1.0 | beats Q3_K* |\n| [GGUF](https://huggingface.co/mradermacher/mini-Cogito-R1-i1-GGUF/resolve/main/mini-Cogito-R1.i1-IQ3_M.gguf) | i1-IQ3_M | 1.0 |  |\n| [GGUF](https://huggingface.co/mradermacher/mini-Cogito-R1-i1-GGUF/resolve/main/mini-Cogito-R1.i1-Q3_K_M.gguf) | i1-Q3_K_M | 1.0 | IQ3_S probably better |\n| [GGUF](https://huggingface.co/mradermacher/mini-Cogito-R1-i1-GGUF/resolve/main/mini-Cogito-R1.i1-Q3_K_L.gguf) | i1-Q3_K_L | 1.1 | IQ3_M probably better |\n| [GGUF](https://huggingface.co/mradermacher/mini-Cogito-R1-i1-GGUF/resolve/main/mini-Cogito-R1.i1-IQ4_XS.gguf) | i1-IQ4_XS | 1.1 |  |\n| [GGUF](https://huggingface.co/mradermacher/mini-Cogito-R1-i1-GGUF/resolve/main/mini-Cogito-R1.i1-IQ4_NL.gguf) | i1-IQ4_NL | 1.2 | prefer IQ4_XS |\n| [GGUF](https://huggingface.co/mradermacher/mini-Cogito-R1-i1-GGUF/resolve/main/mini-Cogito-R1.i1-Q4_0.gguf) | i1-Q4_0 | 1.2 | fast, low quality |\n| [GGUF](https://huggingface.co/mradermacher/mini-Cogito-R1-i1-GGUF/resolve/main/mini-Cogito-R1.i1-Q4_K_S.gguf) | i1-Q4_K_S | 1.2 | optimal size/speed/quality |\n| [GGUF](https://huggingface.co/mradermacher/mini-Cogito-R1-i1-GGUF/resolve/main/mini-Cogito-R1.i1-Q4_K_M.gguf) | i1-Q4_K_M | 1.2 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/mini-Cogito-R1-i1-GGUF/resolve/main/mini-Cogito-R1.i1-Q4_1.gguf) | i1-Q4_1 | 1.3 |  |\n| [GGUF](https://huggingface.co/mradermacher/mini-Cogito-R1-i1-GGUF/resolve/main/mini-Cogito-R1.i1-Q5_K_S.gguf) | i1-Q5_K_S | 1.4 |  |\n| [GGUF](https://huggingface.co/mradermacher/mini-Cogito-R1-i1-GGUF/resolve/main/mini-Cogito-R1.i1-Q5_K_M.gguf) | i1-Q5_K_M | 1.4 |  |\n| [GGUF](https://huggingface.co/mradermacher/mini-Cogito-R1-i1-GGUF/resolve/main/mini-Cogito-R1.i1-Q6_K.gguf) | i1-Q6_K | 1.6 | 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",
    "text-generation-inference",
    "unsloth",
    "qwen2",
    "trl",
    "reasoning",
    "finetune",
    "edge-device",
    "research",
    "en",
    "dataset:bespokelabs/Bespoke-Stratos-17k",
    "dataset:simplescaling/s1K",
    "dataset:cognitivecomputations/dolphin-r1",
    "dataset:openai/gsm8k",
    "dataset:PrimeIntellect/NuminaMath-QwQ-CoT-5M",
    "license:apache-2.0",
    "endpoints_compatible",
    "region:us",
    "imatrix",
    "conversational"
  ],
  "likes": 0,
  "downloads": 392,
  "gated": false,
  "private": false,
  "last_modified": "2025-02-23T11:52:31.000Z",
  "created_at": "2025-02-23T10:34:53.000Z",
  "pipeline_tag": "",
  "library_name": "transformers"
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Source payload excerpt (from Hugging Face API)
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