mradermacher/qwen2.5-7b-instruct-abliterated-v2-gguf overview

{
  "metadata": {},
  "card_data": {
    "base_model": "huihui-ai/Qwen2.5-7B-Instruct-abliterated-v2",
    "language": [
      "zho",
      "eng",
      "fra",
      "spa",
      "por",
      "deu",
      "ita",
      "rus",
      "jpn",
      "kor",
      "vie",
      "tha",
      "ara"
    ],
    "library_name": "transformers",
    "license": "apache-2.0",
    "license_link": "https://huggingface.co/huihui-ai/Qwen2.5-7B-Instruct-abliterated-v2/blob/main/LICENSE",
    "quantized_by": "mradermacher",
    "tags": [
      "chat",
      "abliterated",
      "uncensored"
    ],
    "frontmatter": {
      "base_model": "huihui-ai/Qwen2.5-7B-Instruct-abliterated-v2",
      "language": [
        "zho",
        "eng",
        "fra",
        "spa",
        "por",
        "deu",
        "ita",
        "rus",
        "jpn",
        "kor",
        "vie",
        "tha",
        "ara"
      ],
      "library_name": "transformers",
      "license": "apache-2.0",
      "license_link": "https://huggingface.co/huihui-ai/Qwen2.5-7B-Instruct-abliterated-v2/blob/main/LICENSE",
      "quantized_by": "mradermacher",
      "tags": [
        "chat",
        "abliterated",
        "uncensored"
      ]
    },
    "hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
    "summary": "## About      static quants of https://huggingface.co/huihui-ai/Qwen2.5-7B-Instruct-abliterated-v2  weighted/imatrix quants are available at https://huggingface.co/mradermacher/Qwen2.5-7B-Instruct-abliterated-v2-i1-GGUF",
    "quick_links": [],
    "benchmark_table_html": "",
    "readme_markdown": "---\nbase_model: huihui-ai/Qwen2.5-7B-Instruct-abliterated-v2\nlanguage:\n- zho\n- eng\n- fra\n- spa\n- por\n- deu\n- ita\n- rus\n- jpn\n- kor\n- vie\n- tha\n- ara\nlibrary_name: transformers\nlicense: apache-2.0\nlicense_link: https://huggingface.co/huihui-ai/Qwen2.5-7B-Instruct-abliterated-v2/blob/main/LICENSE\nquantized_by: mradermacher\ntags:\n- chat\n- abliterated\n- uncensored\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/huihui-ai/Qwen2.5-7B-Instruct-abliterated-v2\n\n<!-- provided-files -->\nweighted/imatrix quants are available at https://huggingface.co/mradermacher/Qwen2.5-7B-Instruct-abliterated-v2-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/Qwen2.5-7B-Instruct-abliterated-v2-GGUF/resolve/main/Qwen2.5-7B-Instruct-abliterated-v2.Q2_K.gguf) | Q2_K | 3.1 |  |\n| [GGUF](https://huggingface.co/mradermacher/Qwen2.5-7B-Instruct-abliterated-v2-GGUF/resolve/main/Qwen2.5-7B-Instruct-abliterated-v2.IQ3_XS.gguf) | IQ3_XS | 3.4 |  |\n| [GGUF](https://huggingface.co/mradermacher/Qwen2.5-7B-Instruct-abliterated-v2-GGUF/resolve/main/Qwen2.5-7B-Instruct-abliterated-v2.Q3_K_S.gguf) | Q3_K_S | 3.6 |  |\n| [GGUF](https://huggingface.co/mradermacher/Qwen2.5-7B-Instruct-abliterated-v2-GGUF/resolve/main/Qwen2.5-7B-Instruct-abliterated-v2.IQ3_S.gguf) | IQ3_S | 3.6 | beats Q3_K* |\n| [GGUF](https://huggingface.co/mradermacher/Qwen2.5-7B-Instruct-abliterated-v2-GGUF/resolve/main/Qwen2.5-7B-Instruct-abliterated-v2.IQ3_M.gguf) | IQ3_M | 3.7 |  |\n| [GGUF](https://huggingface.co/mradermacher/Qwen2.5-7B-Instruct-abliterated-v2-GGUF/resolve/main/Qwen2.5-7B-Instruct-abliterated-v2.Q3_K_M.gguf) | Q3_K_M | 3.9 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/Qwen2.5-7B-Instruct-abliterated-v2-GGUF/resolve/main/Qwen2.5-7B-Instruct-abliterated-v2.Q3_K_L.gguf) | Q3_K_L | 4.2 |  |\n| [GGUF](https://huggingface.co/mradermacher/Qwen2.5-7B-Instruct-abliterated-v2-GGUF/resolve/main/Qwen2.5-7B-Instruct-abliterated-v2.IQ4_XS.gguf) | IQ4_XS | 4.4 |  |\n| [GGUF](https://huggingface.co/mradermacher/Qwen2.5-7B-Instruct-abliterated-v2-GGUF/resolve/main/Qwen2.5-7B-Instruct-abliterated-v2.Q4_K_S.gguf) | Q4_K_S | 4.6 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/Qwen2.5-7B-Instruct-abliterated-v2-GGUF/resolve/main/Qwen2.5-7B-Instruct-abliterated-v2.Q4_K_M.gguf) | Q4_K_M | 4.8 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/Qwen2.5-7B-Instruct-abliterated-v2-GGUF/resolve/main/Qwen2.5-7B-Instruct-abliterated-v2.Q5_K_S.gguf) | Q5_K_S | 5.4 |  |\n| [GGUF](https://huggingface.co/mradermacher/Qwen2.5-7B-Instruct-abliterated-v2-GGUF/resolve/main/Qwen2.5-7B-Instruct-abliterated-v2.Q5_K_M.gguf) | Q5_K_M | 5.5 |  |\n| [GGUF](https://huggingface.co/mradermacher/Qwen2.5-7B-Instruct-abliterated-v2-GGUF/resolve/main/Qwen2.5-7B-Instruct-abliterated-v2.Q6_K.gguf) | Q6_K | 6.4 | very good quality |\n| [GGUF](https://huggingface.co/mradermacher/Qwen2.5-7B-Instruct-abliterated-v2-GGUF/resolve/main/Qwen2.5-7B-Instruct-abliterated-v2.Q8_0.gguf) | Q8_0 | 8.2 | fast, best quality |\n| [GGUF](https://huggingface.co/mradermacher/Qwen2.5-7B-Instruct-abliterated-v2-GGUF/resolve/main/Qwen2.5-7B-Instruct-abliterated-v2.f16.gguf) | f16 | 15.3 | 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",
    "chat",
    "abliterated",
    "uncensored",
    "zho",
    "eng",
    "fra",
    "spa",
    "por",
    "deu",
    "ita",
    "rus",
    "jpn",
    "kor",
    "vie",
    "tha",
    "ara",
    "base_model:huihui-ai/Qwen2.5-7B-Instruct-abliterated-v2",
    "base_model:quantized:huihui-ai/Qwen2.5-7B-Instruct-abliterated-v2",
    "license:apache-2.0",
    "endpoints_compatible",
    "region:us",
    "conversational"
  ],
  "likes": 20,
  "downloads": 2552,
  "gated": false,
  "private": false,
  "last_modified": "2025-04-30T13:19:37.000Z",
  "created_at": "2024-09-23T06:45:55.000Z",
  "pipeline_tag": "",
  "library_name": "transformers"
}

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