mradermacher/bggpt-gemma-2-27b-it-v1.0-gguf overview

{
  "metadata": {},
  "card_data": {
    "base_model": "INSAIT-Institute/BgGPT-Gemma-2-27B-IT-v1.0",
    "language": [
      "bg",
      "en"
    ],
    "library_name": "transformers",
    "license": "gemma",
    "quantized_by": "mradermacher",
    "tags": [
      "gemma2",
      "instruct",
      "bggpt",
      "insait"
    ],
    "frontmatter": {
      "base_model": "INSAIT-Institute/BgGPT-Gemma-2-27B-IT-v1.0",
      "language": [
        "bg",
        "en"
      ],
      "library_name": "transformers",
      "license": "gemma",
      "quantized_by": "mradermacher",
      "tags": [
        "gemma2",
        "instruct",
        "bggpt",
        "insait"
      ]
    },
    "hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
    "summary": "## About      static quants of https://huggingface.co/INSAIT-Institute/BgGPT-Gemma-2-27B-IT-v1.0  weighted/imatrix quants are available at https://huggingface.co/mradermacher/BgGPT-Gemma-2-27B-IT-v1.0-i1-GGUF",
    "quick_links": [],
    "benchmark_table_html": "",
    "readme_markdown": "---\nbase_model: INSAIT-Institute/BgGPT-Gemma-2-27B-IT-v1.0\nlanguage:\n- bg\n- en\nlibrary_name: transformers\nlicense: gemma\nquantized_by: mradermacher\ntags:\n- gemma2\n- instruct\n- bggpt\n- insait\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/INSAIT-Institute/BgGPT-Gemma-2-27B-IT-v1.0\n\n<!-- provided-files -->\nweighted/imatrix quants are available at https://huggingface.co/mradermacher/BgGPT-Gemma-2-27B-IT-v1.0-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/BgGPT-Gemma-2-27B-IT-v1.0-GGUF/resolve/main/BgGPT-Gemma-2-27B-IT-v1.0.Q2_K.gguf) | Q2_K | 10.5 |  |\n| [GGUF](https://huggingface.co/mradermacher/BgGPT-Gemma-2-27B-IT-v1.0-GGUF/resolve/main/BgGPT-Gemma-2-27B-IT-v1.0.Q3_K_S.gguf) | Q3_K_S | 12.3 |  |\n| [GGUF](https://huggingface.co/mradermacher/BgGPT-Gemma-2-27B-IT-v1.0-GGUF/resolve/main/BgGPT-Gemma-2-27B-IT-v1.0.Q3_K_M.gguf) | Q3_K_M | 13.5 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/BgGPT-Gemma-2-27B-IT-v1.0-GGUF/resolve/main/BgGPT-Gemma-2-27B-IT-v1.0.Q3_K_L.gguf) | Q3_K_L | 14.6 |  |\n| [GGUF](https://huggingface.co/mradermacher/BgGPT-Gemma-2-27B-IT-v1.0-GGUF/resolve/main/BgGPT-Gemma-2-27B-IT-v1.0.IQ4_XS.gguf) | IQ4_XS | 15.0 |  |\n| [GGUF](https://huggingface.co/mradermacher/BgGPT-Gemma-2-27B-IT-v1.0-GGUF/resolve/main/BgGPT-Gemma-2-27B-IT-v1.0.Q4_K_S.gguf) | Q4_K_S | 15.8 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/BgGPT-Gemma-2-27B-IT-v1.0-GGUF/resolve/main/BgGPT-Gemma-2-27B-IT-v1.0.Q4_K_M.gguf) | Q4_K_M | 16.7 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/BgGPT-Gemma-2-27B-IT-v1.0-GGUF/resolve/main/BgGPT-Gemma-2-27B-IT-v1.0.Q5_K_S.gguf) | Q5_K_S | 19.0 |  |\n| [GGUF](https://huggingface.co/mradermacher/BgGPT-Gemma-2-27B-IT-v1.0-GGUF/resolve/main/BgGPT-Gemma-2-27B-IT-v1.0.Q5_K_M.gguf) | Q5_K_M | 19.5 |  |\n| [GGUF](https://huggingface.co/mradermacher/BgGPT-Gemma-2-27B-IT-v1.0-GGUF/resolve/main/BgGPT-Gemma-2-27B-IT-v1.0.Q6_K.gguf) | Q6_K | 22.4 | very good quality |\n| [GGUF](https://huggingface.co/mradermacher/BgGPT-Gemma-2-27B-IT-v1.0-GGUF/resolve/main/BgGPT-Gemma-2-27B-IT-v1.0.Q8_0.gguf) | Q8_0 | 29.0 | fast, best quality |\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",
    "gemma2",
    "instruct",
    "bggpt",
    "insait",
    "bg",
    "en",
    "base_model:INSAIT-Institute/BgGPT-Gemma-2-27B-IT-v1.0",
    "base_model:quantized:INSAIT-Institute/BgGPT-Gemma-2-27B-IT-v1.0",
    "license:gemma",
    "endpoints_compatible",
    "region:us",
    "conversational"
  ],
  "likes": 0,
  "downloads": 109,
  "gated": false,
  "private": false,
  "last_modified": "2024-11-20T13:11:57.000Z",
  "created_at": "2024-11-20T02:56:26.000Z",
  "pipeline_tag": "",
  "library_name": "transformers"
}

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