nguyenthilaitrieulong/llama-4-scout-17b-16e-instruct-abliterated-gguf overview

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    "base_model": "jiangchengchengNLP/Llama-4-Scout-17B-16E-Instruct-abliterated",
    "language": [
      "ar",
      "de",
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      "es",
      "fr",
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    "library_name": "transformers",
    "license": "llama4",
    "mradermacher": {
      "readme_rev": 1
    },
    "quantized_by": "mradermacher",
    "tags": [
      "facebook",
      "meta",
      "pytorch",
      "llama",
      "llama4"
    ],
    "frontmatter": {
      "base_model": "jiangchengchengNLP/Llama-4-Scout-17B-16E-Instruct-abliterated",
      "language": [
        "ar",
        "de",
        "en",
        "es",
        "fr",
        "hi",
        "id",
        "it",
        "pt",
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        "tl",
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      ],
      "library_name": "transformers",
      "license": "llama4",
      "mradermacher": [],
      "quantized_by": "mradermacher",
      "tags": [
        "facebook",
        "meta",
        "pytorch",
        "llama",
        "llama4"
      ]
    },
    "hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
    "summary": "## About      static quants of https://huggingface.co/jiangchengchengNLP/Llama-4-Scout-17B-16E-Instruct-abliterated  ***For a convenient overview and download list, visit our model page for this model.*** weighted/imatrix quants are available at https://huggingface.co/mradermacher/Llama-4-Scout-17B-16E-Instruct-abliterated-i1-GGUF",
    "quick_links": [],
    "benchmark_table_html": "",
    "readme_markdown": "---\nbase_model: jiangchengchengNLP/Llama-4-Scout-17B-16E-Instruct-abliterated\nlanguage:\n- ar\n- de\n- en\n- es\n- fr\n- hi\n- id\n- it\n- pt\n- th\n- tl\n- vi\nlibrary_name: transformers\nlicense: llama4\nmradermacher:\n  readme_rev: 1\nquantized_by: mradermacher\ntags:\n- facebook\n- meta\n- pytorch\n- llama\n- llama4\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/jiangchengchengNLP/Llama-4-Scout-17B-16E-Instruct-abliterated\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#Llama-4-Scout-17B-16E-Instruct-abliterated-GGUF).***\n\nweighted/imatrix quants are available at https://huggingface.co/mradermacher/Llama-4-Scout-17B-16E-Instruct-abliterated-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/Llama-4-Scout-17B-16E-Instruct-abliterated-GGUF/resolve/main/Llama-4-Scout-17B-16E-Instruct-abliterated.mmproj-Q8_0.gguf) | mmproj-Q8_0 | 1.1 | multi-modal supplement |\n| [GGUF](https://huggingface.co/mradermacher/Llama-4-Scout-17B-16E-Instruct-abliterated-GGUF/resolve/main/Llama-4-Scout-17B-16E-Instruct-abliterated.mmproj-f16.gguf) | mmproj-f16 | 1.9 | multi-modal supplement |\n| [GGUF](https://huggingface.co/mradermacher/Llama-4-Scout-17B-16E-Instruct-abliterated-GGUF/resolve/main/Llama-4-Scout-17B-16E-Instruct-abliterated.Q2_K.gguf) | Q2_K | 39.7 |  |\n| [GGUF](https://huggingface.co/mradermacher/Llama-4-Scout-17B-16E-Instruct-abliterated-GGUF/resolve/main/Llama-4-Scout-17B-16E-Instruct-abliterated.Q3_K_S.gguf) | Q3_K_S | 46.8 |  |\n| [PART 1](https://huggingface.co/mradermacher/Llama-4-Scout-17B-16E-Instruct-abliterated-GGUF/resolve/main/Llama-4-Scout-17B-16E-Instruct-abliterated.Q3_K_M.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/Llama-4-Scout-17B-16E-Instruct-abliterated-GGUF/resolve/main/Llama-4-Scout-17B-16E-Instruct-abliterated.Q3_K_M.gguf.part2of2) | Q3_K_M | 51.9 | lower quality |\n| [PART 1](https://huggingface.co/mradermacher/Llama-4-Scout-17B-16E-Instruct-abliterated-GGUF/resolve/main/Llama-4-Scout-17B-16E-Instruct-abliterated.Q3_K_L.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/Llama-4-Scout-17B-16E-Instruct-abliterated-GGUF/resolve/main/Llama-4-Scout-17B-16E-Instruct-abliterated.Q3_K_L.gguf.part2of2) | Q3_K_L | 56.1 |  |\n| [PART 1](https://huggingface.co/mradermacher/Llama-4-Scout-17B-16E-Instruct-abliterated-GGUF/resolve/main/Llama-4-Scout-17B-16E-Instruct-abliterated.IQ4_XS.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/Llama-4-Scout-17B-16E-Instruct-abliterated-GGUF/resolve/main/Llama-4-Scout-17B-16E-Instruct-abliterated.IQ4_XS.gguf.part2of2) | IQ4_XS | 58.4 |  |\n| [PART 1](https://huggingface.co/mradermacher/Llama-4-Scout-17B-16E-Instruct-abliterated-GGUF/resolve/main/Llama-4-Scout-17B-16E-Instruct-abliterated.Q4_K_S.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/Llama-4-Scout-17B-16E-Instruct-abliterated-GGUF/resolve/main/Llama-4-Scout-17B-16E-Instruct-abliterated.Q4_K_S.gguf.part2of2) | Q4_K_S | 61.6 | fast, recommended |\n| [PART 1](https://huggingface.co/mradermacher/Llama-4-Scout-17B-16E-Instruct-abliterated-GGUF/resolve/main/Llama-4-Scout-17B-16E-Instruct-abliterated.Q4_K_M.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/Llama-4-Scout-17B-16E-Instruct-abliterated-GGUF/resolve/main/Llama-4-Scout-17B-16E-Instruct-abliterated.Q4_K_M.gguf.part2of2) | Q4_K_M | 65.5 | fast, recommended |\n| [PART 1](https://huggingface.co/mradermacher/Llama-4-Scout-17B-16E-Instruct-abliterated-GGUF/resolve/main/Llama-4-Scout-17B-16E-Instruct-abliterated.Q5_K_S.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/Llama-4-Scout-17B-16E-Instruct-abliterated-GGUF/resolve/main/Llama-4-Scout-17B-16E-Instruct-abliterated.Q5_K_S.gguf.part2of2) | Q5_K_S | 74.4 |  |\n| [PART 1](https://huggingface.co/mradermacher/Llama-4-Scout-17B-16E-Instruct-abliterated-GGUF/resolve/main/Llama-4-Scout-17B-16E-Instruct-abliterated.Q5_K_M.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/Llama-4-Scout-17B-16E-Instruct-abliterated-GGUF/resolve/main/Llama-4-Scout-17B-16E-Instruct-abliterated.Q5_K_M.gguf.part2of2) | Q5_K_M | 76.6 |  |\n| [PART 1](https://huggingface.co/mradermacher/Llama-4-Scout-17B-16E-Instruct-abliterated-GGUF/resolve/main/Llama-4-Scout-17B-16E-Instruct-abliterated.Q6_K.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/Llama-4-Scout-17B-16E-Instruct-abliterated-GGUF/resolve/main/Llama-4-Scout-17B-16E-Instruct-abliterated.Q6_K.gguf.part2of2) | Q6_K | 88.5 | very good quality |\n| [PART 1](https://huggingface.co/mradermacher/Llama-4-Scout-17B-16E-Instruct-abliterated-GGUF/resolve/main/Llama-4-Scout-17B-16E-Instruct-abliterated.Q8_0.gguf.part1of3) [PART 2](https://huggingface.co/mradermacher/Llama-4-Scout-17B-16E-Instruct-abliterated-GGUF/resolve/main/Llama-4-Scout-17B-16E-Instruct-abliterated.Q8_0.gguf.part2of3) [PART 3](https://huggingface.co/mradermacher/Llama-4-Scout-17B-16E-Instruct-abliterated-GGUF/resolve/main/Llama-4-Scout-17B-16E-Instruct-abliterated.Q8_0.gguf.part3of3) | Q8_0 | 114.6 | 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",
    "facebook",
    "meta",
    "pytorch",
    "llama",
    "llama4",
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    "en",
    "es",
    "fr",
    "hi",
    "id",
    "it",
    "pt",
    "th",
    "tl",
    "vi",
    "license:llama4",
    "endpoints_compatible",
    "region:us"
  ],
  "likes": 0,
  "downloads": 82,
  "gated": false,
  "private": false,
  "last_modified": "2026-04-09T09:28:18.000Z",
  "created_at": "2026-04-09T09:28:18.000Z",
  "pipeline_tag": "",
  "library_name": "transformers"
}

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