mradermacher/gpt-oss-6.0b-specialized-all-pruned-moe-only-7-experts-gguf overview

{
  "metadata": {},
  "card_data": {
    "base_model": "AmanPriyanshu/gpt-oss-6.0b-specialized-all-pruned-moe-only-7-experts",
    "datasets": [
      "AmanPriyanshu/GPT-OSS-20B-MoE-expert-activations"
    ],
    "language": [
      "en"
    ],
    "library_name": "transformers",
    "license": "apache-2.0",
    "mradermacher": {
      "readme_rev": 1
    },
    "quantized_by": "mradermacher",
    "tags": [
      "mixture-of-experts",
      "moe",
      "expert-pruning",
      "gpt-oss",
      "openai",
      "reasoning",
      "all",
      "specialized",
      "efficient",
      "transformer",
      "causal-lm",
      "text-generation",
      "pytorch",
      "pruned-model",
      "domain-specific"
    ],
    "frontmatter": {
      "base_model": "AmanPriyanshu/gpt-oss-6.0b-specialized-all-pruned-moe-only-7-experts",
      "datasets": [
        "AmanPriyanshu/GPT-OSS-20B-MoE-expert-activations"
      ],
      "language": [
        "en"
      ],
      "library_name": "transformers",
      "license": "apache-2.0",
      "mradermacher": [],
      "quantized_by": "mradermacher",
      "tags": [
        "mixture-of-experts",
        "moe",
        "expert-pruning",
        "gpt-oss",
        "openai",
        "reasoning",
        "all",
        "specialized",
        "efficient",
        "transformer",
        "causal-lm",
        "text-generation",
        "pytorch",
        "pruned-model",
        "domain-specific"
      ]
    },
    "hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
    "summary": "## About         static quants of https://huggingface.co/AmanPriyanshu/gpt-oss-6.0b-specialized-all-pruned-moe-only-7-experts  ***For a convenient overview and download list, visit our model page for this model.*** weighted/imatrix quants are available at https://huggingface.co/mradermacher/gpt-oss-6.0b-specialized-all-pruned-moe-only-7-experts-i1-GGUF",
    "quick_links": [],
    "benchmark_table_html": "",
    "readme_markdown": "---\nbase_model: AmanPriyanshu/gpt-oss-6.0b-specialized-all-pruned-moe-only-7-experts\ndatasets:\n- AmanPriyanshu/GPT-OSS-20B-MoE-expert-activations\nlanguage:\n- en\nlibrary_name: transformers\nlicense: apache-2.0\nmradermacher:\n  readme_rev: 1\nquantized_by: mradermacher\ntags:\n- mixture-of-experts\n- moe\n- expert-pruning\n- gpt-oss\n- openai\n- reasoning\n- all\n- specialized\n- efficient\n- transformer\n- causal-lm\n- text-generation\n- pytorch\n- pruned-model\n- domain-specific\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/AmanPriyanshu/gpt-oss-6.0b-specialized-all-pruned-moe-only-7-experts\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#gpt-oss-6.0b-specialized-all-pruned-moe-only-7-experts-GGUF).***\n\nweighted/imatrix quants are available at https://huggingface.co/mradermacher/gpt-oss-6.0b-specialized-all-pruned-moe-only-7-experts-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/gpt-oss-6.0b-specialized-all-pruned-moe-only-7-experts-GGUF/resolve/main/gpt-oss-6.0b-specialized-all-pruned-moe-only-7-experts.Q3_K_S.gguf) | Q3_K_S | 3.7 |  |\n| [GGUF](https://huggingface.co/mradermacher/gpt-oss-6.0b-specialized-all-pruned-moe-only-7-experts-GGUF/resolve/main/gpt-oss-6.0b-specialized-all-pruned-moe-only-7-experts.Q2_K.gguf) | Q2_K | 3.7 |  |\n| [GGUF](https://huggingface.co/mradermacher/gpt-oss-6.0b-specialized-all-pruned-moe-only-7-experts-GGUF/resolve/main/gpt-oss-6.0b-specialized-all-pruned-moe-only-7-experts.IQ4_XS.gguf) | IQ4_XS | 3.8 |  |\n| [GGUF](https://huggingface.co/mradermacher/gpt-oss-6.0b-specialized-all-pruned-moe-only-7-experts-GGUF/resolve/main/gpt-oss-6.0b-specialized-all-pruned-moe-only-7-experts.Q3_K_M.gguf) | Q3_K_M | 4.0 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/gpt-oss-6.0b-specialized-all-pruned-moe-only-7-experts-GGUF/resolve/main/gpt-oss-6.0b-specialized-all-pruned-moe-only-7-experts.Q3_K_L.gguf) | Q3_K_L | 4.1 |  |\n| [GGUF](https://huggingface.co/mradermacher/gpt-oss-6.0b-specialized-all-pruned-moe-only-7-experts-GGUF/resolve/main/gpt-oss-6.0b-specialized-all-pruned-moe-only-7-experts.Q4_K_S.gguf) | Q4_K_S | 4.4 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/gpt-oss-6.0b-specialized-all-pruned-moe-only-7-experts-GGUF/resolve/main/gpt-oss-6.0b-specialized-all-pruned-moe-only-7-experts.Q4_K_M.gguf) | Q4_K_M | 4.7 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/gpt-oss-6.0b-specialized-all-pruned-moe-only-7-experts-GGUF/resolve/main/gpt-oss-6.0b-specialized-all-pruned-moe-only-7-experts.Q5_K_S.gguf) | Q5_K_S | 4.8 |  |\n| [GGUF](https://huggingface.co/mradermacher/gpt-oss-6.0b-specialized-all-pruned-moe-only-7-experts-GGUF/resolve/main/gpt-oss-6.0b-specialized-all-pruned-moe-only-7-experts.Q5_K_M.gguf) | Q5_K_M | 5.0 |  |\n| [GGUF](https://huggingface.co/mradermacher/gpt-oss-6.0b-specialized-all-pruned-moe-only-7-experts-GGUF/resolve/main/gpt-oss-6.0b-specialized-all-pruned-moe-only-7-experts.Q6_K.gguf) | Q6_K | 6.4 | very good quality |\n| [GGUF](https://huggingface.co/mradermacher/gpt-oss-6.0b-specialized-all-pruned-moe-only-7-experts-GGUF/resolve/main/gpt-oss-6.0b-specialized-all-pruned-moe-only-7-experts.Q8_0.gguf) | Q8_0 | 6.5 | fast, best quality |\n| [GGUF](https://huggingface.co/mradermacher/gpt-oss-6.0b-specialized-all-pruned-moe-only-7-experts-GGUF/resolve/main/gpt-oss-6.0b-specialized-all-pruned-moe-only-7-experts.f16.gguf) | f16 | 12.1 | 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",
    "mixture-of-experts",
    "moe",
    "expert-pruning",
    "gpt-oss",
    "openai",
    "reasoning",
    "all",
    "specialized",
    "efficient",
    "transformer",
    "causal-lm",
    "text-generation",
    "pytorch",
    "pruned-model",
    "domain-specific",
    "en",
    "dataset:AmanPriyanshu/GPT-OSS-20B-MoE-expert-activations",
    "base_model:AmanPriyanshu/gpt-oss-6.0b-specialized-all-pruned-moe-only-7-experts",
    "base_model:quantized:AmanPriyanshu/gpt-oss-6.0b-specialized-all-pruned-moe-only-7-experts",
    "license:apache-2.0",
    "endpoints_compatible",
    "region:us",
    "conversational"
  ],
  "likes": 2,
  "downloads": 291,
  "gated": false,
  "private": false,
  "last_modified": "2025-09-11T17:34:17.000Z",
  "created_at": "2025-09-11T12:00:16.000Z",
  "pipeline_tag": "text-generation",
  "library_name": "transformers"
}

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