mradermacher/deepseek-r1-strategy-qwen-2.5-1.5b-unstructured-to-structured-gguf overview

{
  "metadata": {},
  "card_data": {
    "base_model": "MasterControlAIML/DeepSeek-R1-Strategy-Qwen-2.5-1.5b-Unstructured-To-Structured",
    "datasets": [
      "bhaviktheslider/JSON-Unstructured-Structured"
    ],
    "language": [
      "en"
    ],
    "library_name": "transformers",
    "license": "apache-2.0",
    "model_name": null,
    "quantized_by": "mradermacher",
    "tags": [
      "generated_from_trainer",
      "trl",
      "grpo",
      "deepseek",
      "r1"
    ],
    "frontmatter": {
      "base_model": "MasterControlAIML/DeepSeek-R1-Strategy-Qwen-2.5-1.5b-Unstructured-To-Structured",
      "datasets": [
        "bhaviktheslider/JSON-Unstructured-Structured"
      ],
      "language": [
        "en"
      ],
      "library_name": "transformers",
      "license": "apache-2.0",
      "model_name": "~",
      "quantized_by": "mradermacher",
      "tags": [
        "generated_from_trainer",
        "trl",
        "grpo",
        "deepseek",
        "r1"
      ]
    },
    "hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
    "summary": "## About      static quants of https://huggingface.co/MasterControlAIML/DeepSeek-R1-Strategy-Qwen-2.5-1.5b-Unstructured-To-Structured  weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.",
    "quick_links": [],
    "benchmark_table_html": "",
    "readme_markdown": "---\nbase_model: MasterControlAIML/DeepSeek-R1-Strategy-Qwen-2.5-1.5b-Unstructured-To-Structured\ndatasets:\n- bhaviktheslider/JSON-Unstructured-Structured\nlanguage:\n- en\nlibrary_name: transformers\nlicense: apache-2.0\nmodel_name: ~\nquantized_by: mradermacher\ntags:\n- generated_from_trainer\n- trl\n- grpo\n- deepseek\n- r1\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/MasterControlAIML/DeepSeek-R1-Strategy-Qwen-2.5-1.5b-Unstructured-To-Structured\n\n<!-- provided-files -->\nweighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.\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/DeepSeek-R1-Strategy-Qwen-2.5-1.5b-Unstructured-To-Structured-GGUF/resolve/main/DeepSeek-R1-Strategy-Qwen-2.5-1.5b-Unstructured-To-Structured.Q2_K.gguf) | Q2_K | 0.8 |  |\n| [GGUF](https://huggingface.co/mradermacher/DeepSeek-R1-Strategy-Qwen-2.5-1.5b-Unstructured-To-Structured-GGUF/resolve/main/DeepSeek-R1-Strategy-Qwen-2.5-1.5b-Unstructured-To-Structured.Q3_K_S.gguf) | Q3_K_S | 0.9 |  |\n| [GGUF](https://huggingface.co/mradermacher/DeepSeek-R1-Strategy-Qwen-2.5-1.5b-Unstructured-To-Structured-GGUF/resolve/main/DeepSeek-R1-Strategy-Qwen-2.5-1.5b-Unstructured-To-Structured.Q3_K_M.gguf) | Q3_K_M | 0.9 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/DeepSeek-R1-Strategy-Qwen-2.5-1.5b-Unstructured-To-Structured-GGUF/resolve/main/DeepSeek-R1-Strategy-Qwen-2.5-1.5b-Unstructured-To-Structured.Q3_K_L.gguf) | Q3_K_L | 1.0 |  |\n| [GGUF](https://huggingface.co/mradermacher/DeepSeek-R1-Strategy-Qwen-2.5-1.5b-Unstructured-To-Structured-GGUF/resolve/main/DeepSeek-R1-Strategy-Qwen-2.5-1.5b-Unstructured-To-Structured.IQ4_XS.gguf) | IQ4_XS | 1.0 |  |\n| [GGUF](https://huggingface.co/mradermacher/DeepSeek-R1-Strategy-Qwen-2.5-1.5b-Unstructured-To-Structured-GGUF/resolve/main/DeepSeek-R1-Strategy-Qwen-2.5-1.5b-Unstructured-To-Structured.Q4_K_S.gguf) | Q4_K_S | 1.0 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/DeepSeek-R1-Strategy-Qwen-2.5-1.5b-Unstructured-To-Structured-GGUF/resolve/main/DeepSeek-R1-Strategy-Qwen-2.5-1.5b-Unstructured-To-Structured.Q4_K_M.gguf) | Q4_K_M | 1.1 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/DeepSeek-R1-Strategy-Qwen-2.5-1.5b-Unstructured-To-Structured-GGUF/resolve/main/DeepSeek-R1-Strategy-Qwen-2.5-1.5b-Unstructured-To-Structured.Q5_K_S.gguf) | Q5_K_S | 1.2 |  |\n| [GGUF](https://huggingface.co/mradermacher/DeepSeek-R1-Strategy-Qwen-2.5-1.5b-Unstructured-To-Structured-GGUF/resolve/main/DeepSeek-R1-Strategy-Qwen-2.5-1.5b-Unstructured-To-Structured.Q5_K_M.gguf) | Q5_K_M | 1.2 |  |\n| [GGUF](https://huggingface.co/mradermacher/DeepSeek-R1-Strategy-Qwen-2.5-1.5b-Unstructured-To-Structured-GGUF/resolve/main/DeepSeek-R1-Strategy-Qwen-2.5-1.5b-Unstructured-To-Structured.Q6_K.gguf) | Q6_K | 1.4 | very good quality |\n| [GGUF](https://huggingface.co/mradermacher/DeepSeek-R1-Strategy-Qwen-2.5-1.5b-Unstructured-To-Structured-GGUF/resolve/main/DeepSeek-R1-Strategy-Qwen-2.5-1.5b-Unstructured-To-Structured.Q8_0.gguf) | Q8_0 | 1.7 | fast, best quality |\n| [GGUF](https://huggingface.co/mradermacher/DeepSeek-R1-Strategy-Qwen-2.5-1.5b-Unstructured-To-Structured-GGUF/resolve/main/DeepSeek-R1-Strategy-Qwen-2.5-1.5b-Unstructured-To-Structured.f16.gguf) | f16 | 3.2 | 16 bpw, overkill |\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",
    "generated_from_trainer",
    "trl",
    "grpo",
    "deepseek",
    "r1",
    "en",
    "dataset:bhaviktheslider/JSON-Unstructured-Structured",
    "base_model:MasterControlAIML/DeepSeek-R1-Strategy-Qwen-2.5-1.5b-Unstructured-To-Structured",
    "base_model:quantized:MasterControlAIML/DeepSeek-R1-Strategy-Qwen-2.5-1.5b-Unstructured-To-Structured",
    "license:apache-2.0",
    "endpoints_compatible",
    "region:us",
    "conversational"
  ],
  "likes": 2,
  "downloads": 165,
  "gated": false,
  "private": false,
  "last_modified": "2025-02-03T14:05:38.000Z",
  "created_at": "2025-02-01T05:22:32.000Z",
  "pipeline_tag": "",
  "library_name": "transformers"
}

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