mradermacher/sanad-1.0-gguf overview

{
  "metadata": {},
  "card_data": {
    "base_model": "360kaUser/Sanad-1.0",
    "datasets": [
      "akemiH/NoteChat",
      "starmpcc/Asclepius-Synthetic-Clinical-Notes",
      "AGBonnet/augmented-clinical-notes",
      "omi-health/medical-dialogue-to-soap-summary",
      "openlifescienceai/medmcqa",
      "GBaker/MedQA-USMLE-4-options",
      "zhengyun21/PMC-Patients",
      "lingshu-medical-mllm/ReasonMed",
      "UCSC-VLAA/MedReason",
      "FreedomIntelligence/medical-o1-reasoning-SFT",
      "qiaojin/PubMedQA",
      "appier-ai-research/StreamBench",
      "MustafaIbrahim/medical-arabic-qa",
      "MKamil/arabic_medical_50k"
    ],
    "language": [
      "en",
      "ar"
    ],
    "library_name": "transformers",
    "license": "apache-2.0",
    "mradermacher": {
      "readme_rev": 1
    },
    "quantized_by": "mradermacher",
    "tags": [
      "medical",
      "clinical-ai",
      "medgemma",
      "fine-tuned",
      "diagnosis",
      "differential-diagnosis",
      "clinical-transcription",
      "arabic-medical",
      "qlora",
      "healthcare",
      "gemma3_text"
    ],
    "frontmatter": {
      "base_model": "360kaUser/Sanad-1.0",
      "datasets": [
        "akemiH/NoteChat",
        "starmpcc/Asclepius-Synthetic-Clinical-Notes",
        "AGBonnet/augmented-clinical-notes",
        "omi-health/medical-dialogue-to-soap-summary",
        "openlifescienceai/medmcqa",
        "GBaker/MedQA-USMLE-4-options",
        "zhengyun21/PMC-Patients",
        "lingshu-medical-mllm/ReasonMed",
        "UCSC-VLAA/MedReason",
        "FreedomIntelligence/medical-o1-reasoning-SFT",
        "qiaojin/PubMedQA",
        "appier-ai-research/StreamBench",
        "MustafaIbrahim/medical-arabic-qa",
        "MKamil/arabic_medical_50k"
      ],
      "language": [
        "en",
        "ar"
      ],
      "library_name": "transformers",
      "license": "apache-2.0",
      "mradermacher": [],
      "quantized_by": "mradermacher",
      "tags": [
        "medical",
        "clinical-ai",
        "medgemma",
        "fine-tuned",
        "diagnosis",
        "differential-diagnosis",
        "clinical-transcription",
        "arabic-medical",
        "qlora",
        "healthcare",
        "gemma3_text"
      ]
    },
    "hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
    "summary": "## About         static quants of https://huggingface.co/360kaUser/Sanad-1.0  ***For a convenient overview and download list, visit our model page for this model.*** weighted/imatrix quants are available at https://huggingface.co/mradermacher/Sanad-1.0-i1-GGUF",
    "quick_links": [],
    "benchmark_table_html": "",
    "readme_markdown": "---\nbase_model: 360kaUser/Sanad-1.0\ndatasets:\n- akemiH/NoteChat\n- starmpcc/Asclepius-Synthetic-Clinical-Notes\n- AGBonnet/augmented-clinical-notes\n- omi-health/medical-dialogue-to-soap-summary\n- openlifescienceai/medmcqa\n- GBaker/MedQA-USMLE-4-options\n- zhengyun21/PMC-Patients\n- lingshu-medical-mllm/ReasonMed\n- UCSC-VLAA/MedReason\n- FreedomIntelligence/medical-o1-reasoning-SFT\n- qiaojin/PubMedQA\n- appier-ai-research/StreamBench\n- MustafaIbrahim/medical-arabic-qa\n- MKamil/arabic_medical_50k\nlanguage:\n- en\n- ar\nlibrary_name: transformers\nlicense: apache-2.0\nmradermacher:\n  readme_rev: 1\nquantized_by: mradermacher\ntags:\n- medical\n- clinical-ai\n- medgemma\n- fine-tuned\n- diagnosis\n- differential-diagnosis\n- clinical-transcription\n- arabic-medical\n- qlora\n- healthcare\n- gemma3_text\n---\n## About\n\n<!-- ### quantize_version: 2 -->\n<!-- ### output_tensor_quantised: 1 -->\n<!-- ### convert_type: hf -->\n<!-- ### vocab_type:  -->\n<!-- ### tags:  -->\n<!-- ### quants:  x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->\n<!-- ### quants_skip:  -->\n<!-- ### skip_mmproj:  -->\nstatic quants of https://huggingface.co/360kaUser/Sanad-1.0\n\n<!-- provided-files -->\n\n***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#Sanad-1.0-GGUF).***\n\nweighted/imatrix quants are available at https://huggingface.co/mradermacher/Sanad-1.0-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/Sanad-1.0-GGUF/resolve/main/Sanad-1.0.Q2_K.gguf) | Q2_K | 10.6 |  |\n| [GGUF](https://huggingface.co/mradermacher/Sanad-1.0-GGUF/resolve/main/Sanad-1.0.Q3_K_S.gguf) | Q3_K_S | 12.3 |  |\n| [GGUF](https://huggingface.co/mradermacher/Sanad-1.0-GGUF/resolve/main/Sanad-1.0.Q3_K_M.gguf) | Q3_K_M | 13.5 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/Sanad-1.0-GGUF/resolve/main/Sanad-1.0.Q3_K_L.gguf) | Q3_K_L | 14.6 |  |\n| [GGUF](https://huggingface.co/mradermacher/Sanad-1.0-GGUF/resolve/main/Sanad-1.0.IQ4_XS.gguf) | IQ4_XS | 15.0 |  |\n| [GGUF](https://huggingface.co/mradermacher/Sanad-1.0-GGUF/resolve/main/Sanad-1.0.Q4_K_S.gguf) | Q4_K_S | 15.8 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/Sanad-1.0-GGUF/resolve/main/Sanad-1.0.Q4_K_M.gguf) | Q4_K_M | 16.6 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/Sanad-1.0-GGUF/resolve/main/Sanad-1.0.Q5_K_S.gguf) | Q5_K_S | 18.9 |  |\n| [GGUF](https://huggingface.co/mradermacher/Sanad-1.0-GGUF/resolve/main/Sanad-1.0.Q5_K_M.gguf) | Q5_K_M | 19.4 |  |\n| [GGUF](https://huggingface.co/mradermacher/Sanad-1.0-GGUF/resolve/main/Sanad-1.0.Q6_K.gguf) | Q6_K | 22.3 | very good quality |\n| [GGUF](https://huggingface.co/mradermacher/Sanad-1.0-GGUF/resolve/main/Sanad-1.0.Q8_0.gguf) | Q8_0 | 28.8 | 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",
    "medical",
    "clinical-ai",
    "medgemma",
    "fine-tuned",
    "diagnosis",
    "differential-diagnosis",
    "clinical-transcription",
    "arabic-medical",
    "qlora",
    "healthcare",
    "gemma3_text",
    "en",
    "ar",
    "dataset:akemiH/NoteChat",
    "dataset:starmpcc/Asclepius-Synthetic-Clinical-Notes",
    "dataset:AGBonnet/augmented-clinical-notes",
    "dataset:omi-health/medical-dialogue-to-soap-summary",
    "dataset:openlifescienceai/medmcqa",
    "dataset:GBaker/MedQA-USMLE-4-options",
    "dataset:zhengyun21/PMC-Patients",
    "dataset:lingshu-medical-mllm/ReasonMed",
    "dataset:UCSC-VLAA/MedReason",
    "dataset:FreedomIntelligence/medical-o1-reasoning-SFT",
    "dataset:qiaojin/PubMedQA",
    "dataset:appier-ai-research/StreamBench",
    "dataset:MustafaIbrahim/medical-arabic-qa",
    "dataset:MKamil/arabic_medical_50k",
    "base_model:360kaUser/Sanad-1.0",
    "base_model:quantized:360kaUser/Sanad-1.0",
    "license:apache-2.0",
    "endpoints_compatible",
    "region:us",
    "conversational"
  ],
  "likes": 0,
  "downloads": 418,
  "gated": false,
  "private": false,
  "last_modified": "2026-03-25T04:47:49.000Z",
  "created_at": "2026-03-24T13:02:53.000Z",
  "pipeline_tag": "",
  "library_name": "transformers"
}

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  "lastModified": "2026-03-25T04:47:49.000Z",
  "author": "mradermacher",
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