mradermacher/spyazweb_ai_deepmind_project-i1-gguf overview

{
  "metadata": {},
  "card_data": {
    "base_model": "LeroyDyer/SpyazWeb_AI_DeepMind_Project",
    "datasets": [
      "gretelai/synthetic_text_to_sql",
      "HuggingFaceTB/cosmopedia",
      "teknium/OpenHermes-2.5",
      "Open-Orca/SlimOrca",
      "Open-Orca/OpenOrca",
      "cognitivecomputations/dolphin-coder",
      "databricks/databricks-dolly-15k",
      "yahma/alpaca-cleaned",
      "uonlp/CulturaX",
      "mwitiderrick/SwahiliPlatypus",
      "swahili",
      "Rogendo/English-Swahili-Sentence-Pairs",
      "ise-uiuc/Magicoder-Evol-Instruct-110K",
      "meta-math/MetaMathQA",
      "abacusai/ARC_DPO_FewShot",
      "abacusai/MetaMath_DPO_FewShot",
      "abacusai/HellaSwag_DPO_FewShot",
      "HaltiaAI/Her-The-Movie-Samantha-and-Theodore-Dataset",
      "gretelai/synthetic_text_to_sql",
      "HuggingFaceTB/cosmopedia",
      "teknium/OpenHermes-2.5",
      "cognitivecomputations/dolphin-coder",
      "databricks/databricks-dolly-15k",
      "yahma/alpaca-cleaned",
      "uonlp/CulturaX",
      "mwitiderrick/SwahiliPlatypus",
      "swahili",
      "Rogendo/English-Swahili-Sentence-Pairs",
      "ise-uiuc/Magicoder-Evol-Instruct-110K",
      "meta-math/MetaMathQA"
    ],
    "language": [
      "en"
    ],
    "library_name": "transformers",
    "license": "apache-2.0",
    "quantized_by": "mradermacher",
    "tags": [
      "text-generation-inference",
      "transformers",
      "leaderboard",
      "mistral",
      "trl"
    ],
    "frontmatter": {
      "base_model": "LeroyDyer/SpyazWeb_AI_DeepMind_Project",
      "datasets": [
        "gretelai/synthetic_text_to_sql",
        "HuggingFaceTB/cosmopedia",
        "teknium/OpenHermes-2.5",
        "Open-Orca/SlimOrca",
        "Open-Orca/OpenOrca",
        "cognitivecomputations/dolphin-coder",
        "databricks/databricks-dolly-15k",
        "yahma/alpaca-cleaned",
        "uonlp/CulturaX",
        "mwitiderrick/SwahiliPlatypus",
        "swahili",
        "Rogendo/English-Swahili-Sentence-Pairs",
        "ise-uiuc/Magicoder-Evol-Instruct-110K",
        "meta-math/MetaMathQA",
        "abacusai/ARC_DPO_FewShot",
        "abacusai/MetaMath_DPO_FewShot",
        "abacusai/HellaSwag_DPO_FewShot",
        "HaltiaAI/Her-The-Movie-Samantha-and-Theodore-Dataset",
        "gretelai/synthetic_text_to_sql",
        "HuggingFaceTB/cosmopedia",
        "teknium/OpenHermes-2.5",
        "cognitivecomputations/dolphin-coder",
        "databricks/databricks-dolly-15k",
        "yahma/alpaca-cleaned",
        "uonlp/CulturaX",
        "mwitiderrick/SwahiliPlatypus",
        "swahili",
        "Rogendo/English-Swahili-Sentence-Pairs",
        "ise-uiuc/Magicoder-Evol-Instruct-110K",
        "meta-math/MetaMathQA"
      ],
      "language": [
        "en"
      ],
      "library_name": "transformers",
      "license": "apache-2.0",
      "quantized_by": "mradermacher",
      "tags": [
        "text-generation-inference",
        "transformers",
        "leaderboard",
        "mistral",
        "trl"
      ]
    },
    "hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
    "summary": "## About      weighted/imatrix quants of https://huggingface.co/LeroyDyer/SpyazWeb_AI_DeepMind_Project  static quants are available at https://huggingface.co/mradermacher/SpyazWeb_AI_DeepMind_Project-GGUF",
    "quick_links": [],
    "benchmark_table_html": "",
    "readme_markdown": "---\nbase_model: LeroyDyer/SpyazWeb_AI_DeepMind_Project\ndatasets:\n- gretelai/synthetic_text_to_sql\n- HuggingFaceTB/cosmopedia\n- teknium/OpenHermes-2.5\n- Open-Orca/SlimOrca\n- Open-Orca/OpenOrca\n- cognitivecomputations/dolphin-coder\n- databricks/databricks-dolly-15k\n- yahma/alpaca-cleaned\n- uonlp/CulturaX\n- mwitiderrick/SwahiliPlatypus\n- swahili\n- Rogendo/English-Swahili-Sentence-Pairs\n- ise-uiuc/Magicoder-Evol-Instruct-110K\n- meta-math/MetaMathQA\n- abacusai/ARC_DPO_FewShot\n- abacusai/MetaMath_DPO_FewShot\n- abacusai/HellaSwag_DPO_FewShot\n- HaltiaAI/Her-The-Movie-Samantha-and-Theodore-Dataset\n- gretelai/synthetic_text_to_sql\n- HuggingFaceTB/cosmopedia\n- teknium/OpenHermes-2.5\n- cognitivecomputations/dolphin-coder\n- databricks/databricks-dolly-15k\n- yahma/alpaca-cleaned\n- uonlp/CulturaX\n- mwitiderrick/SwahiliPlatypus\n- swahili\n- Rogendo/English-Swahili-Sentence-Pairs\n- ise-uiuc/Magicoder-Evol-Instruct-110K\n- meta-math/MetaMathQA\nlanguage:\n- en\nlibrary_name: transformers\nlicense: apache-2.0\nquantized_by: mradermacher\ntags:\n- text-generation-inference\n- transformers\n- leaderboard\n- mistral\n- trl\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/LeroyDyer/SpyazWeb_AI_DeepMind_Project\n\n<!-- provided-files -->\nstatic quants are available at https://huggingface.co/mradermacher/SpyazWeb_AI_DeepMind_Project-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/SpyazWeb_AI_DeepMind_Project-i1-GGUF/resolve/main/SpyazWeb_AI_DeepMind_Project.i1-IQ1_S.gguf) | i1-IQ1_S | 1.7 | for the desperate |\n| [GGUF](https://huggingface.co/mradermacher/SpyazWeb_AI_DeepMind_Project-i1-GGUF/resolve/main/SpyazWeb_AI_DeepMind_Project.i1-IQ1_M.gguf) | i1-IQ1_M | 1.9 | mostly desperate |\n| [GGUF](https://huggingface.co/mradermacher/SpyazWeb_AI_DeepMind_Project-i1-GGUF/resolve/main/SpyazWeb_AI_DeepMind_Project.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 2.1 |  |\n| [GGUF](https://huggingface.co/mradermacher/SpyazWeb_AI_DeepMind_Project-i1-GGUF/resolve/main/SpyazWeb_AI_DeepMind_Project.i1-IQ2_XS.gguf) | i1-IQ2_XS | 2.3 |  |\n| [GGUF](https://huggingface.co/mradermacher/SpyazWeb_AI_DeepMind_Project-i1-GGUF/resolve/main/SpyazWeb_AI_DeepMind_Project.i1-IQ2_S.gguf) | i1-IQ2_S | 2.4 |  |\n| [GGUF](https://huggingface.co/mradermacher/SpyazWeb_AI_DeepMind_Project-i1-GGUF/resolve/main/SpyazWeb_AI_DeepMind_Project.i1-IQ2_M.gguf) | i1-IQ2_M | 2.6 |  |\n| [GGUF](https://huggingface.co/mradermacher/SpyazWeb_AI_DeepMind_Project-i1-GGUF/resolve/main/SpyazWeb_AI_DeepMind_Project.i1-Q2_K_S.gguf) | i1-Q2_K_S | 2.6 | very low quality |\n| [GGUF](https://huggingface.co/mradermacher/SpyazWeb_AI_DeepMind_Project-i1-GGUF/resolve/main/SpyazWeb_AI_DeepMind_Project.i1-Q2_K.gguf) | i1-Q2_K | 2.8 | IQ3_XXS probably better |\n| [GGUF](https://huggingface.co/mradermacher/SpyazWeb_AI_DeepMind_Project-i1-GGUF/resolve/main/SpyazWeb_AI_DeepMind_Project.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 2.9 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/SpyazWeb_AI_DeepMind_Project-i1-GGUF/resolve/main/SpyazWeb_AI_DeepMind_Project.i1-IQ3_XS.gguf) | i1-IQ3_XS | 3.1 |  |\n| [GGUF](https://huggingface.co/mradermacher/SpyazWeb_AI_DeepMind_Project-i1-GGUF/resolve/main/SpyazWeb_AI_DeepMind_Project.i1-Q3_K_S.gguf) | i1-Q3_K_S | 3.3 | IQ3_XS probably better |\n| [GGUF](https://huggingface.co/mradermacher/SpyazWeb_AI_DeepMind_Project-i1-GGUF/resolve/main/SpyazWeb_AI_DeepMind_Project.i1-IQ3_S.gguf) | i1-IQ3_S | 3.3 | beats Q3_K* |\n| [GGUF](https://huggingface.co/mradermacher/SpyazWeb_AI_DeepMind_Project-i1-GGUF/resolve/main/SpyazWeb_AI_DeepMind_Project.i1-IQ3_M.gguf) | i1-IQ3_M | 3.4 |  |\n| [GGUF](https://huggingface.co/mradermacher/SpyazWeb_AI_DeepMind_Project-i1-GGUF/resolve/main/SpyazWeb_AI_DeepMind_Project.i1-Q3_K_M.gguf) | i1-Q3_K_M | 3.6 | IQ3_S probably better |\n| [GGUF](https://huggingface.co/mradermacher/SpyazWeb_AI_DeepMind_Project-i1-GGUF/resolve/main/SpyazWeb_AI_DeepMind_Project.i1-Q3_K_L.gguf) | i1-Q3_K_L | 3.9 | IQ3_M probably better |\n| [GGUF](https://huggingface.co/mradermacher/SpyazWeb_AI_DeepMind_Project-i1-GGUF/resolve/main/SpyazWeb_AI_DeepMind_Project.i1-IQ4_XS.gguf) | i1-IQ4_XS | 4.0 |  |\n| [GGUF](https://huggingface.co/mradermacher/SpyazWeb_AI_DeepMind_Project-i1-GGUF/resolve/main/SpyazWeb_AI_DeepMind_Project.i1-Q4_0.gguf) | i1-Q4_0 | 4.2 | fast, low quality |\n| [GGUF](https://huggingface.co/mradermacher/SpyazWeb_AI_DeepMind_Project-i1-GGUF/resolve/main/SpyazWeb_AI_DeepMind_Project.i1-IQ4_NL.gguf) | i1-IQ4_NL | 4.2 | prefer IQ4_XS |\n| [GGUF](https://huggingface.co/mradermacher/SpyazWeb_AI_DeepMind_Project-i1-GGUF/resolve/main/SpyazWeb_AI_DeepMind_Project.i1-Q4_K_S.gguf) | i1-Q4_K_S | 4.2 | optimal size/speed/quality |\n| [GGUF](https://huggingface.co/mradermacher/SpyazWeb_AI_DeepMind_Project-i1-GGUF/resolve/main/SpyazWeb_AI_DeepMind_Project.i1-Q4_K_M.gguf) | i1-Q4_K_M | 4.5 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/SpyazWeb_AI_DeepMind_Project-i1-GGUF/resolve/main/SpyazWeb_AI_DeepMind_Project.i1-Q4_1.gguf) | i1-Q4_1 | 4.7 |  |\n| [GGUF](https://huggingface.co/mradermacher/SpyazWeb_AI_DeepMind_Project-i1-GGUF/resolve/main/SpyazWeb_AI_DeepMind_Project.i1-Q5_K_S.gguf) | i1-Q5_K_S | 5.1 |  |\n| [GGUF](https://huggingface.co/mradermacher/SpyazWeb_AI_DeepMind_Project-i1-GGUF/resolve/main/SpyazWeb_AI_DeepMind_Project.i1-Q5_K_M.gguf) | i1-Q5_K_M | 5.2 |  |\n| [GGUF](https://huggingface.co/mradermacher/SpyazWeb_AI_DeepMind_Project-i1-GGUF/resolve/main/SpyazWeb_AI_DeepMind_Project.i1-Q6_K.gguf) | i1-Q6_K | 6.0 | 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",
    "leaderboard",
    "mistral",
    "trl",
    "en",
    "dataset:gretelai/synthetic_text_to_sql",
    "dataset:HuggingFaceTB/cosmopedia",
    "dataset:teknium/OpenHermes-2.5",
    "dataset:Open-Orca/SlimOrca",
    "dataset:Open-Orca/OpenOrca",
    "dataset:cognitivecomputations/dolphin-coder",
    "dataset:databricks/databricks-dolly-15k",
    "dataset:yahma/alpaca-cleaned",
    "dataset:uonlp/CulturaX",
    "dataset:mwitiderrick/SwahiliPlatypus",
    "dataset:swahili",
    "dataset:Rogendo/English-Swahili-Sentence-Pairs",
    "dataset:ise-uiuc/Magicoder-Evol-Instruct-110K",
    "dataset:meta-math/MetaMathQA",
    "dataset:abacusai/ARC_DPO_FewShot",
    "dataset:abacusai/MetaMath_DPO_FewShot",
    "dataset:abacusai/HellaSwag_DPO_FewShot",
    "dataset:HaltiaAI/Her-The-Movie-Samantha-and-Theodore-Dataset",
    "base_model:LeroyDyer/SpyazWeb_AI_DeepMind_Project",
    "base_model:quantized:LeroyDyer/SpyazWeb_AI_DeepMind_Project",
    "license:apache-2.0",
    "endpoints_compatible",
    "region:us",
    "imatrix"
  ],
  "likes": 1,
  "downloads": 831,
  "gated": false,
  "private": false,
  "last_modified": "2025-01-19T08:23:59.000Z",
  "created_at": "2025-01-19T07:56:01.000Z",
  "pipeline_tag": "",
  "library_name": "transformers"
}

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