mradermacher/gemma-2-27b-it-i1-gguf overview

{
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  "card_data": {
    "base_model": "google/gemma-2-27b-it",
    "extra_gated_button_content": "Acknowledge license",
    "extra_gated_heading": "Access Gemma on Hugging Face",
    "extra_gated_prompt": "To access Gemma on Hugging Face, you’re required to review and agree to Google’s usage license. To do this, please ensure you’re logged in to Hugging Face and click below. Requests are processed immediately.",
    "language": [
      "en"
    ],
    "library_name": "transformers",
    "license": "gemma",
    "quantized_by": "mradermacher",
    "frontmatter": {
      "base_model": "google/gemma-2-27b-it",
      "extra_gated_button_content": "Acknowledge license",
      "extra_gated_heading": "Access Gemma on Hugging Face",
      "extra_gated_prompt": "To access Gemma on Hugging Face, you’re required to review and",
      "language": [
        "en"
      ],
      "library_name": "transformers",
      "license": "gemma",
      "quantized_by": "mradermacher"
    },
    "hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
    "summary": "## About      weighted/imatrix quants of https://huggingface.co/google/gemma-2-27b-it  static quants are available at https://huggingface.co/mradermacher/gemma-2-27b-it-GGUF",
    "quick_links": [],
    "benchmark_table_html": "",
    "readme_markdown": "---\nbase_model: google/gemma-2-27b-it\nextra_gated_button_content: Acknowledge license\nextra_gated_heading: Access Gemma on Hugging Face\nextra_gated_prompt: To access Gemma on Hugging Face, you’re required to review and\n  agree to Google’s usage license. To do this, please ensure you’re logged in to Hugging\n  Face and click below. Requests are processed immediately.\nlanguage:\n- en\nlibrary_name: transformers\nlicense: gemma\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/google/gemma-2-27b-it\n\n<!-- provided-files -->\nstatic quants are available at https://huggingface.co/mradermacher/gemma-2-27b-it-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/gemma-2-27b-it-i1-GGUF/resolve/main/gemma-2-27b-it.i1-IQ1_S.gguf) | i1-IQ1_S | 6.2 | for the desperate |\n| [GGUF](https://huggingface.co/mradermacher/gemma-2-27b-it-i1-GGUF/resolve/main/gemma-2-27b-it.i1-IQ1_M.gguf) | i1-IQ1_M | 6.8 | mostly desperate |\n| [GGUF](https://huggingface.co/mradermacher/gemma-2-27b-it-i1-GGUF/resolve/main/gemma-2-27b-it.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 7.7 |  |\n| [GGUF](https://huggingface.co/mradermacher/gemma-2-27b-it-i1-GGUF/resolve/main/gemma-2-27b-it.i1-IQ2_XS.gguf) | i1-IQ2_XS | 8.5 |  |\n| [GGUF](https://huggingface.co/mradermacher/gemma-2-27b-it-i1-GGUF/resolve/main/gemma-2-27b-it.i1-IQ2_S.gguf) | i1-IQ2_S | 8.8 |  |\n| [GGUF](https://huggingface.co/mradermacher/gemma-2-27b-it-i1-GGUF/resolve/main/gemma-2-27b-it.i1-IQ2_M.gguf) | i1-IQ2_M | 9.5 |  |\n| [GGUF](https://huggingface.co/mradermacher/gemma-2-27b-it-i1-GGUF/resolve/main/gemma-2-27b-it.i1-Q2_K.gguf) | i1-Q2_K | 10.5 | IQ3_XXS probably better |\n| [GGUF](https://huggingface.co/mradermacher/gemma-2-27b-it-i1-GGUF/resolve/main/gemma-2-27b-it.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 10.9 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/gemma-2-27b-it-i1-GGUF/resolve/main/gemma-2-27b-it.i1-IQ3_XS.gguf) | i1-IQ3_XS | 11.7 |  |\n| [GGUF](https://huggingface.co/mradermacher/gemma-2-27b-it-i1-GGUF/resolve/main/gemma-2-27b-it.i1-IQ3_S.gguf) | i1-IQ3_S | 12.3 | beats Q3_K* |\n| [GGUF](https://huggingface.co/mradermacher/gemma-2-27b-it-i1-GGUF/resolve/main/gemma-2-27b-it.i1-Q3_K_S.gguf) | i1-Q3_K_S | 12.3 | IQ3_XS probably better |\n| [GGUF](https://huggingface.co/mradermacher/gemma-2-27b-it-i1-GGUF/resolve/main/gemma-2-27b-it.i1-IQ3_M.gguf) | i1-IQ3_M | 12.6 |  |\n| [GGUF](https://huggingface.co/mradermacher/gemma-2-27b-it-i1-GGUF/resolve/main/gemma-2-27b-it.i1-Q3_K_M.gguf) | i1-Q3_K_M | 13.5 | IQ3_S probably better |\n| [GGUF](https://huggingface.co/mradermacher/gemma-2-27b-it-i1-GGUF/resolve/main/gemma-2-27b-it.i1-Q3_K_L.gguf) | i1-Q3_K_L | 14.6 | IQ3_M probably better |\n| [GGUF](https://huggingface.co/mradermacher/gemma-2-27b-it-i1-GGUF/resolve/main/gemma-2-27b-it.i1-IQ4_XS.gguf) | i1-IQ4_XS | 14.9 |  |\n| [GGUF](https://huggingface.co/mradermacher/gemma-2-27b-it-i1-GGUF/resolve/main/gemma-2-27b-it.i1-Q4_0.gguf) | i1-Q4_0 | 15.8 | fast, low quality |\n| [GGUF](https://huggingface.co/mradermacher/gemma-2-27b-it-i1-GGUF/resolve/main/gemma-2-27b-it.i1-Q4_K_S.gguf) | i1-Q4_K_S | 15.8 | optimal size/speed/quality |\n| [GGUF](https://huggingface.co/mradermacher/gemma-2-27b-it-i1-GGUF/resolve/main/gemma-2-27b-it.i1-Q4_K_M.gguf) | i1-Q4_K_M | 16.7 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/gemma-2-27b-it-i1-GGUF/resolve/main/gemma-2-27b-it.i1-Q5_K_S.gguf) | i1-Q5_K_S | 19.0 |  |\n| [GGUF](https://huggingface.co/mradermacher/gemma-2-27b-it-i1-GGUF/resolve/main/gemma-2-27b-it.i1-Q5_K_M.gguf) | i1-Q5_K_M | 19.5 |  |\n| [GGUF](https://huggingface.co/mradermacher/gemma-2-27b-it-i1-GGUF/resolve/main/gemma-2-27b-it.i1-Q6_K.gguf) | i1-Q6_K | 22.4 | 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",
    "en",
    "base_model:google/gemma-2-27b-it",
    "base_model:quantized:google/gemma-2-27b-it",
    "license:gemma",
    "endpoints_compatible",
    "region:us",
    "imatrix",
    "conversational"
  ],
  "likes": 2,
  "downloads": 265,
  "gated": false,
  "private": false,
  "last_modified": "2024-08-02T10:00:25.000Z",
  "created_at": "2024-07-02T01:22:19.000Z",
  "pipeline_tag": "",
  "library_name": "transformers"
}

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