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mradermacher/reyna-cot-4b-v0.1-i1-gguf overview

About weighted/imatrix quants of https://huggingface.co/aloobun/Reyna-CoT-4B-v0.1 static quants are available at https://huggingface.co/mradermacher/Reyna-CoT-4B-v0.1-GGUF

transformersgguffinetunesynthetic datacustom_codeqwen2COTendataset:kaist-ai/CoT-Collectionbase_model:aloobun/Reyna-CoT-4B-v0.1base_model:quantized:aloobun/Reyna-CoT-4B-v0.1license:otherendpoints_compatibleregion:usimatrixconversational
mradermacher/reyna-cot-4b-v0.1-i1-gguf visual
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146
Likes
0
Pipeline
Library
transformers
Visibility
Public
Access
Open

Repository Files & Downloads

24 files detected
Direct downloads for all repository files
FileTypeQuantizationSizeLink
Reyna-CoT-4B-v0.1.i1-IQ1_M.gguf GGUF IQ1_M 1.07 GB Download
Reyna-CoT-4B-v0.1.i1-IQ1_S.gguf GGUF IQ1_S 1.01 GB Download
Reyna-CoT-4B-v0.1.i1-IQ2_M.gguf GGUF IQ2_M 1.42 GB Download
Reyna-CoT-4B-v0.1.i1-IQ2_S.gguf GGUF IQ2_S 1.35 GB Download
Reyna-CoT-4B-v0.1.i1-IQ2_XS.gguf GGUF IQ2_XS 1.24 GB Download
Reyna-CoT-4B-v0.1.i1-IQ2_XXS.gguf GGUF IQ2_XXS 1.16 GB Download
Reyna-CoT-4B-v0.1.i1-IQ3_M.gguf GGUF IQ3_M 1.81 GB Download
Reyna-CoT-4B-v0.1.i1-IQ3_S.gguf GGUF IQ3_S 1.73 GB Download
Reyna-CoT-4B-v0.1.i1-IQ3_XS.gguf GGUF IQ3_XS 1.66 GB Download
Reyna-CoT-4B-v0.1.i1-IQ3_XXS.gguf GGUF IQ3_XXS 1.52 GB Download
Reyna-CoT-4B-v0.1.i1-IQ4_XS.gguf GGUF IQ4_XS 2.07 GB Download
Reyna-CoT-4B-v0.1.i1-Q2_K.gguf GGUF Q2_K 1.51 GB Download
Reyna-CoT-4B-v0.1.i1-Q3_K_L.gguf GGUF Q3_K_L 2.03 GB Download
Reyna-CoT-4B-v0.1.i1-Q3_K_M.gguf GGUF Q3_K_M 1.89 GB Download
Reyna-CoT-4B-v0.1.i1-Q3_K_S.gguf GGUF Q3_K_S 1.73 GB Download
Reyna-CoT-4B-v0.1.i1-Q4_0.gguf GGUF 2.18 GB Download
Reyna-CoT-4B-v0.1.i1-Q4_0_4_4.gguf GGUF 2.17 GB Download
Reyna-CoT-4B-v0.1.i1-Q4_0_4_8.gguf GGUF 2.17 GB Download
Reyna-CoT-4B-v0.1.i1-Q4_0_8_8.gguf GGUF 2.17 GB Download
Reyna-CoT-4B-v0.1.i1-Q4_K_M.gguf GGUF Q4_K_M 2.29 GB Download
Reyna-CoT-4B-v0.1.i1-Q4_K_S.gguf GGUF Q4_K_S 2.18 GB Download
Reyna-CoT-4B-v0.1.i1-Q5_K_M.gguf GGUF Q5_K_M 2.64 GB Download
Reyna-CoT-4B-v0.1.i1-Q5_K_S.gguf GGUF Q5_K_S 2.58 GB Download
Reyna-CoT-4B-v0.1.i1-Q6_K.gguf GGUF Q6_K 3.03 GB Download

Model Details Live

Model Slug
mradermacher/reyna-cot-4b-v0.1-i1-gguf
Author
mradermacher
Pipeline Task
Library
transformers
Created
2024-11-10
Last Modified
2024-11-10
Gated
No
Private
No
HF SHA
0d6fcd0c492c8375e787337c30662f38eab03da1
License
other
Language
en
Base Model
aloobun/Reyna-CoT-4B-v0.1

Metadata Inspector

Normalized metadata (stored in metadata_json)
{
  "metadata": {},
  "card_data": {
    "base_model": "aloobun/Reyna-CoT-4B-v0.1",
    "datasets": [
      "kaist-ai/CoT-Collection"
    ],
    "language": [
      "en"
    ],
    "library_name": "transformers",
    "license": "other",
    "license_link": "https://huggingface.co/Qwen/Qwen1.5-1.8B-Chat/raw/main/LICENSE",
    "license_name": "tongyi-qianwen-research",
    "quantized_by": "mradermacher",
    "tags": [
      "finetune",
      "synthetic data",
      "custom_code",
      "qwen2",
      "COT"
    ],
    "frontmatter": {
      "base_model": "aloobun/Reyna-CoT-4B-v0.1",
      "datasets": [
        "kaist-ai/CoT-Collection"
      ],
      "language": [
        "en"
      ],
      "library_name": "transformers",
      "license": "other",
      "license_link": "https://huggingface.co/Qwen/Qwen1.5-1.8B-Chat/raw/main/LICENSE",
      "license_name": "tongyi-qianwen-research",
      "quantized_by": "mradermacher",
      "tags": [
        "finetune",
        "synthetic data",
        "custom_code",
        "qwen2",
        "COT"
      ]
    },
    "hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
    "summary": "## About      weighted/imatrix quants of https://huggingface.co/aloobun/Reyna-CoT-4B-v0.1  static quants are available at https://huggingface.co/mradermacher/Reyna-CoT-4B-v0.1-GGUF",
    "quick_links": [],
    "benchmark_table_html": "",
    "readme_markdown": "---\nbase_model: aloobun/Reyna-CoT-4B-v0.1\ndatasets:\n- kaist-ai/CoT-Collection\nlanguage:\n- en\nlibrary_name: transformers\nlicense: other\nlicense_link: https://huggingface.co/Qwen/Qwen1.5-1.8B-Chat/raw/main/LICENSE\nlicense_name: tongyi-qianwen-research\nquantized_by: mradermacher\ntags:\n- finetune\n- synthetic data\n- custom_code\n- qwen2\n- COT\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/aloobun/Reyna-CoT-4B-v0.1\n\n<!-- provided-files -->\nstatic quants are available at https://huggingface.co/mradermacher/Reyna-CoT-4B-v0.1-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/Reyna-CoT-4B-v0.1-i1-GGUF/resolve/main/Reyna-CoT-4B-v0.1.i1-IQ1_S.gguf) | i1-IQ1_S | 1.2 | for the desperate |\n| [GGUF](https://huggingface.co/mradermacher/Reyna-CoT-4B-v0.1-i1-GGUF/resolve/main/Reyna-CoT-4B-v0.1.i1-IQ1_M.gguf) | i1-IQ1_M | 1.2 | mostly desperate |\n| [GGUF](https://huggingface.co/mradermacher/Reyna-CoT-4B-v0.1-i1-GGUF/resolve/main/Reyna-CoT-4B-v0.1.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 1.3 |  |\n| [GGUF](https://huggingface.co/mradermacher/Reyna-CoT-4B-v0.1-i1-GGUF/resolve/main/Reyna-CoT-4B-v0.1.i1-IQ2_XS.gguf) | i1-IQ2_XS | 1.4 |  |\n| [GGUF](https://huggingface.co/mradermacher/Reyna-CoT-4B-v0.1-i1-GGUF/resolve/main/Reyna-CoT-4B-v0.1.i1-IQ2_S.gguf) | i1-IQ2_S | 1.5 |  |\n| [GGUF](https://huggingface.co/mradermacher/Reyna-CoT-4B-v0.1-i1-GGUF/resolve/main/Reyna-CoT-4B-v0.1.i1-IQ2_M.gguf) | i1-IQ2_M | 1.6 |  |\n| [GGUF](https://huggingface.co/mradermacher/Reyna-CoT-4B-v0.1-i1-GGUF/resolve/main/Reyna-CoT-4B-v0.1.i1-Q2_K.gguf) | i1-Q2_K | 1.7 | IQ3_XXS probably better |\n| [GGUF](https://huggingface.co/mradermacher/Reyna-CoT-4B-v0.1-i1-GGUF/resolve/main/Reyna-CoT-4B-v0.1.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 1.7 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/Reyna-CoT-4B-v0.1-i1-GGUF/resolve/main/Reyna-CoT-4B-v0.1.i1-IQ3_XS.gguf) | i1-IQ3_XS | 1.9 |  |\n| [GGUF](https://huggingface.co/mradermacher/Reyna-CoT-4B-v0.1-i1-GGUF/resolve/main/Reyna-CoT-4B-v0.1.i1-IQ3_S.gguf) | i1-IQ3_S | 2.0 | beats Q3_K* |\n| [GGUF](https://huggingface.co/mradermacher/Reyna-CoT-4B-v0.1-i1-GGUF/resolve/main/Reyna-CoT-4B-v0.1.i1-Q3_K_S.gguf) | i1-Q3_K_S | 2.0 | IQ3_XS probably better |\n| [GGUF](https://huggingface.co/mradermacher/Reyna-CoT-4B-v0.1-i1-GGUF/resolve/main/Reyna-CoT-4B-v0.1.i1-IQ3_M.gguf) | i1-IQ3_M | 2.0 |  |\n| [GGUF](https://huggingface.co/mradermacher/Reyna-CoT-4B-v0.1-i1-GGUF/resolve/main/Reyna-CoT-4B-v0.1.i1-Q3_K_M.gguf) | i1-Q3_K_M | 2.1 | IQ3_S probably better |\n| [GGUF](https://huggingface.co/mradermacher/Reyna-CoT-4B-v0.1-i1-GGUF/resolve/main/Reyna-CoT-4B-v0.1.i1-Q3_K_L.gguf) | i1-Q3_K_L | 2.3 | IQ3_M probably better |\n| [GGUF](https://huggingface.co/mradermacher/Reyna-CoT-4B-v0.1-i1-GGUF/resolve/main/Reyna-CoT-4B-v0.1.i1-IQ4_XS.gguf) | i1-IQ4_XS | 2.3 |  |\n| [GGUF](https://huggingface.co/mradermacher/Reyna-CoT-4B-v0.1-i1-GGUF/resolve/main/Reyna-CoT-4B-v0.1.i1-Q4_0_4_4.gguf) | i1-Q4_0_4_4 | 2.4 | fast on arm, low quality |\n| [GGUF](https://huggingface.co/mradermacher/Reyna-CoT-4B-v0.1-i1-GGUF/resolve/main/Reyna-CoT-4B-v0.1.i1-Q4_0_4_8.gguf) | i1-Q4_0_4_8 | 2.4 | fast on arm+i8mm, low quality |\n| [GGUF](https://huggingface.co/mradermacher/Reyna-CoT-4B-v0.1-i1-GGUF/resolve/main/Reyna-CoT-4B-v0.1.i1-Q4_0_8_8.gguf) | i1-Q4_0_8_8 | 2.4 | fast on arm+sve, low quality |\n| [GGUF](https://huggingface.co/mradermacher/Reyna-CoT-4B-v0.1-i1-GGUF/resolve/main/Reyna-CoT-4B-v0.1.i1-Q4_0.gguf) | i1-Q4_0 | 2.4 | fast, low quality |\n| [GGUF](https://huggingface.co/mradermacher/Reyna-CoT-4B-v0.1-i1-GGUF/resolve/main/Reyna-CoT-4B-v0.1.i1-Q4_K_S.gguf) | i1-Q4_K_S | 2.4 | optimal size/speed/quality |\n| [GGUF](https://huggingface.co/mradermacher/Reyna-CoT-4B-v0.1-i1-GGUF/resolve/main/Reyna-CoT-4B-v0.1.i1-Q4_K_M.gguf) | i1-Q4_K_M | 2.6 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/Reyna-CoT-4B-v0.1-i1-GGUF/resolve/main/Reyna-CoT-4B-v0.1.i1-Q5_K_S.gguf) | i1-Q5_K_S | 2.9 |  |\n| [GGUF](https://huggingface.co/mradermacher/Reyna-CoT-4B-v0.1-i1-GGUF/resolve/main/Reyna-CoT-4B-v0.1.i1-Q5_K_M.gguf) | i1-Q5_K_M | 2.9 |  |\n| [GGUF](https://huggingface.co/mradermacher/Reyna-CoT-4B-v0.1-i1-GGUF/resolve/main/Reyna-CoT-4B-v0.1.i1-Q6_K.gguf) | i1-Q6_K | 3.3 | 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",
    "finetune",
    "synthetic data",
    "custom_code",
    "qwen2",
    "COT",
    "en",
    "dataset:kaist-ai/CoT-Collection",
    "base_model:aloobun/Reyna-CoT-4B-v0.1",
    "base_model:quantized:aloobun/Reyna-CoT-4B-v0.1",
    "license:other",
    "endpoints_compatible",
    "region:us",
    "imatrix",
    "conversational"
  ],
  "likes": 0,
  "downloads": 146,
  "gated": false,
  "private": false,
  "last_modified": "2024-11-10T12:07:12.000Z",
  "created_at": "2024-11-10T10:46:18.000Z",
  "pipeline_tag": "",
  "library_name": "transformers"
}
Source payload excerpt (from Hugging Face API)
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  "createdAt": "2024-11-10T10:46:18.000Z",
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