mradermacher/qwen3-17b-qiming-v1.0-total-recall-medium-gguf overview

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  "card_data": {
    "base_model": "DavidAU/Qwen3-17B-QiMing-V1.0-Total-Recall-Medium",
    "language": [
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      "fr",
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    "library_name": "transformers",
    "license": "apache-2.0",
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      "readme_rev": 1
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    "quantized_by": "mradermacher",
    "tags": [
      "programming",
      "code generation",
      "code",
      "codeqwen",
      "programming",
      "code generation",
      "code",
      "codeqwen",
      "moe",
      "coding",
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      "chat",
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      "optional thinking",
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      "all use cases",
      "QiMing",
      "QiMing-holos",
      "bagua",
      "decision-making",
      "strategic-analysis",
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      "chat",
      "philosophy-driven-ai"
    ],
    "frontmatter": {
      "base_model": "DavidAU/Qwen3-17B-QiMing-V1.0-Total-Recall-Medium",
      "language": [
        "en",
        "fr",
        "zh",
        "de"
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      "library_name": "transformers",
      "license": "apache-2.0",
      "mradermacher": [],
      "quantized_by": "mradermacher",
      "tags": [
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        "code generation",
        "code",
        "codeqwen",
        "programming",
        "code generation",
        "code",
        "codeqwen",
        "moe",
        "coding",
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        "qwen2",
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        "brainstorm 20x",
        "brainstorm",
        "optional thinking",
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        "all use cases",
        "QiMing",
        "QiMing-holos",
        "bagua",
        "decision-making",
        "strategic-analysis",
        "cognitive-architecture",
        "chat",
        "philosophy-driven-ai"
      ]
    },
    "hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
    "summary": "## About         static quants of https://huggingface.co/DavidAU/Qwen3-17B-QiMing-V1.0-Total-Recall-Medium  ***For a convenient overview and download list, visit our model page for this model.*** weighted/imatrix quants are available at https://huggingface.co/mradermacher/Qwen3-17B-QiMing-V1.0-Total-Recall-Medium-i1-GGUF",
    "quick_links": [],
    "benchmark_table_html": "",
    "readme_markdown": "---\nbase_model: DavidAU/Qwen3-17B-QiMing-V1.0-Total-Recall-Medium\nlanguage:\n- en\n- fr\n- zh\n- de\nlibrary_name: transformers\nlicense: apache-2.0\nmradermacher:\n  readme_rev: 1\nquantized_by: mradermacher\ntags:\n- programming\n- code generation\n- code\n- codeqwen\n- programming\n- code generation\n- code\n- codeqwen\n- moe\n- coding\n- coder\n- qwen2\n- chat\n- qwen\n- qwen-coder\n- chat\n- qwen\n- qwen-coder\n- qwen3\n- finetune\n- brainstorm 20x\n- brainstorm\n- optional thinking\n- creative\n- all use cases\n- QiMing\n- QiMing-holos\n- bagua\n- decision-making\n- strategic-analysis\n- cognitive-architecture\n- chat\n- philosophy-driven-ai\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/DavidAU/Qwen3-17B-QiMing-V1.0-Total-Recall-Medium\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#Qwen3-17B-QiMing-V1.0-Total-Recall-Medium-GGUF).***\n\nweighted/imatrix quants are available at https://huggingface.co/mradermacher/Qwen3-17B-QiMing-V1.0-Total-Recall-Medium-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/Qwen3-17B-QiMing-V1.0-Total-Recall-Medium-GGUF/resolve/main/Qwen3-17B-QiMing-V1.0-Total-Recall-Medium.Q2_K.gguf) | Q2_K | 6.7 |  |\n| [GGUF](https://huggingface.co/mradermacher/Qwen3-17B-QiMing-V1.0-Total-Recall-Medium-GGUF/resolve/main/Qwen3-17B-QiMing-V1.0-Total-Recall-Medium.Q3_K_S.gguf) | Q3_K_S | 7.8 |  |\n| [GGUF](https://huggingface.co/mradermacher/Qwen3-17B-QiMing-V1.0-Total-Recall-Medium-GGUF/resolve/main/Qwen3-17B-QiMing-V1.0-Total-Recall-Medium.Q3_K_M.gguf) | Q3_K_M | 8.5 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/Qwen3-17B-QiMing-V1.0-Total-Recall-Medium-GGUF/resolve/main/Qwen3-17B-QiMing-V1.0-Total-Recall-Medium.Q3_K_L.gguf) | Q3_K_L | 9.2 |  |\n| [GGUF](https://huggingface.co/mradermacher/Qwen3-17B-QiMing-V1.0-Total-Recall-Medium-GGUF/resolve/main/Qwen3-17B-QiMing-V1.0-Total-Recall-Medium.IQ4_XS.gguf) | IQ4_XS | 9.5 |  |\n| [GGUF](https://huggingface.co/mradermacher/Qwen3-17B-QiMing-V1.0-Total-Recall-Medium-GGUF/resolve/main/Qwen3-17B-QiMing-V1.0-Total-Recall-Medium.Q4_K_S.gguf) | Q4_K_S | 10.0 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/Qwen3-17B-QiMing-V1.0-Total-Recall-Medium-GGUF/resolve/main/Qwen3-17B-QiMing-V1.0-Total-Recall-Medium.Q4_K_M.gguf) | Q4_K_M | 10.5 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/Qwen3-17B-QiMing-V1.0-Total-Recall-Medium-GGUF/resolve/main/Qwen3-17B-QiMing-V1.0-Total-Recall-Medium.Q5_K_S.gguf) | Q5_K_S | 12.0 |  |\n| [GGUF](https://huggingface.co/mradermacher/Qwen3-17B-QiMing-V1.0-Total-Recall-Medium-GGUF/resolve/main/Qwen3-17B-QiMing-V1.0-Total-Recall-Medium.Q5_K_M.gguf) | Q5_K_M | 12.2 |  |\n| [GGUF](https://huggingface.co/mradermacher/Qwen3-17B-QiMing-V1.0-Total-Recall-Medium-GGUF/resolve/main/Qwen3-17B-QiMing-V1.0-Total-Recall-Medium.Q6_K.gguf) | Q6_K | 14.1 | very good quality |\n| [GGUF](https://huggingface.co/mradermacher/Qwen3-17B-QiMing-V1.0-Total-Recall-Medium-GGUF/resolve/main/Qwen3-17B-QiMing-V1.0-Total-Recall-Medium.Q8_0.gguf) | Q8_0 | 18.3 | 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",
    "programming",
    "code generation",
    "code",
    "codeqwen",
    "moe",
    "coding",
    "coder",
    "qwen2",
    "chat",
    "qwen",
    "qwen-coder",
    "qwen3",
    "finetune",
    "brainstorm 20x",
    "brainstorm",
    "optional thinking",
    "creative",
    "all use cases",
    "QiMing",
    "QiMing-holos",
    "bagua",
    "decision-making",
    "strategic-analysis",
    "cognitive-architecture",
    "philosophy-driven-ai",
    "en",
    "fr",
    "zh",
    "de",
    "base_model:DavidAU/Qwen3-17B-QiMing-V1.0-Total-Recall-Medium",
    "base_model:quantized:DavidAU/Qwen3-17B-QiMing-V1.0-Total-Recall-Medium",
    "license:apache-2.0",
    "endpoints_compatible",
    "region:us",
    "conversational"
  ],
  "likes": 0,
  "downloads": 150,
  "gated": false,
  "private": false,
  "last_modified": "2025-09-02T13:42:07.000Z",
  "created_at": "2025-09-02T11:28:16.000Z",
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  "library_name": "transformers"
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