mradermacher/xiaolong-qwen3-0.6b-i1-gguf overview

{
  "metadata": {},
  "card_data": {
    "base_model": "nbeerbower/Xiaolong-Qwen3-0.6B",
    "datasets": [
      "nbeerbower/GreatFirewall-DPO",
      "nbeerbower/Schule-DPO",
      "nbeerbower/Purpura-DPO",
      "nbeerbower/Arkhaios-DPO",
      "jondurbin/truthy-dpo-v0.1",
      "antiven0m/physical-reasoning-dpo",
      "flammenai/Date-DPO-NoAsterisks",
      "flammenai/Prude-Phi3-DPO",
      "Atsunori/HelpSteer2-DPO",
      "jondurbin/gutenberg-dpo-v0.1",
      "nbeerbower/gutenberg2-dpo",
      "nbeerbower/gutenberg-moderne-dpo",
      "GeneralReasoning/GeneralThought-430K",
      "nvidia/OpenMathReasoning",
      "nvidia/OpenCodeReasoning"
    ],
    "language": [
      "en"
    ],
    "library_name": "transformers",
    "license": "apache-2.0",
    "mradermacher": {
      "readme_rev": 1
    },
    "quantized_by": "mradermacher",
    "tags": [
      "orpo",
      "uncensored",
      "reasoning",
      "cot"
    ],
    "frontmatter": {
      "base_model": "nbeerbower/Xiaolong-Qwen3-0.6B",
      "datasets": [
        "nbeerbower/GreatFirewall-DPO",
        "nbeerbower/Schule-DPO",
        "nbeerbower/Purpura-DPO",
        "nbeerbower/Arkhaios-DPO",
        "jondurbin/truthy-dpo-v0.1",
        "antiven0m/physical-reasoning-dpo",
        "flammenai/Date-DPO-NoAsterisks",
        "flammenai/Prude-Phi3-DPO",
        "Atsunori/HelpSteer2-DPO",
        "jondurbin/gutenberg-dpo-v0.1",
        "nbeerbower/gutenberg2-dpo",
        "nbeerbower/gutenberg-moderne-dpo",
        "GeneralReasoning/GeneralThought-430K",
        "nvidia/OpenMathReasoning",
        "nvidia/OpenCodeReasoning"
      ],
      "language": [
        "en"
      ],
      "library_name": "transformers",
      "license": "apache-2.0",
      "mradermacher": [],
      "quantized_by": "mradermacher",
      "tags": [
        "orpo",
        "uncensored",
        "reasoning",
        "cot"
      ]
    },
    "hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
    "summary": "## About      weighted/imatrix quants of https://huggingface.co/nbeerbower/Xiaolong-Qwen3-0.6B  ***For a convenient overview and download list, visit our model page for this model.*** static quants are available at https://huggingface.co/mradermacher/Xiaolong-Qwen3-0.6B-GGUF",
    "quick_links": [],
    "benchmark_table_html": "",
    "readme_markdown": "---\nbase_model: nbeerbower/Xiaolong-Qwen3-0.6B\ndatasets:\n- nbeerbower/GreatFirewall-DPO\n- nbeerbower/Schule-DPO\n- nbeerbower/Purpura-DPO\n- nbeerbower/Arkhaios-DPO\n- jondurbin/truthy-dpo-v0.1\n- antiven0m/physical-reasoning-dpo\n- flammenai/Date-DPO-NoAsterisks\n- flammenai/Prude-Phi3-DPO\n- Atsunori/HelpSteer2-DPO\n- jondurbin/gutenberg-dpo-v0.1\n- nbeerbower/gutenberg2-dpo\n- nbeerbower/gutenberg-moderne-dpo\n- GeneralReasoning/GeneralThought-430K\n- nvidia/OpenMathReasoning\n- nvidia/OpenCodeReasoning\nlanguage:\n- en\nlibrary_name: transformers\nlicense: apache-2.0\nmradermacher:\n  readme_rev: 1\nquantized_by: mradermacher\ntags:\n- orpo\n- uncensored\n- reasoning\n- cot\n---\n## About\n\n<!-- ### quantize_version: 2 -->\n<!-- ### output_tensor_quantised: 1 -->\n<!-- ### convert_type: hf -->\n<!-- ### vocab_type:  -->\n<!-- ### tags: nicoboss -->\nweighted/imatrix quants of https://huggingface.co/nbeerbower/Xiaolong-Qwen3-0.6B\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#Xiaolong-Qwen3-0.6B-i1-GGUF).***\n\nstatic quants are available at https://huggingface.co/mradermacher/Xiaolong-Qwen3-0.6B-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/Xiaolong-Qwen3-0.6B-i1-GGUF/resolve/main/Xiaolong-Qwen3-0.6B.i1-IQ1_S.gguf) | i1-IQ1_S | 0.3 | for the desperate |\n| [GGUF](https://huggingface.co/mradermacher/Xiaolong-Qwen3-0.6B-i1-GGUF/resolve/main/Xiaolong-Qwen3-0.6B.i1-IQ1_M.gguf) | i1-IQ1_M | 0.3 | mostly desperate |\n| [GGUF](https://huggingface.co/mradermacher/Xiaolong-Qwen3-0.6B-i1-GGUF/resolve/main/Xiaolong-Qwen3-0.6B.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 0.3 |  |\n| [GGUF](https://huggingface.co/mradermacher/Xiaolong-Qwen3-0.6B-i1-GGUF/resolve/main/Xiaolong-Qwen3-0.6B.i1-IQ2_XS.gguf) | i1-IQ2_XS | 0.3 |  |\n| [GGUF](https://huggingface.co/mradermacher/Xiaolong-Qwen3-0.6B-i1-GGUF/resolve/main/Xiaolong-Qwen3-0.6B.i1-IQ2_S.gguf) | i1-IQ2_S | 0.4 |  |\n| [GGUF](https://huggingface.co/mradermacher/Xiaolong-Qwen3-0.6B-i1-GGUF/resolve/main/Xiaolong-Qwen3-0.6B.i1-IQ2_M.gguf) | i1-IQ2_M | 0.4 |  |\n| [GGUF](https://huggingface.co/mradermacher/Xiaolong-Qwen3-0.6B-i1-GGUF/resolve/main/Xiaolong-Qwen3-0.6B.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 0.4 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/Xiaolong-Qwen3-0.6B-i1-GGUF/resolve/main/Xiaolong-Qwen3-0.6B.i1-Q2_K_S.gguf) | i1-Q2_K_S | 0.4 | very low quality |\n| [GGUF](https://huggingface.co/mradermacher/Xiaolong-Qwen3-0.6B-i1-GGUF/resolve/main/Xiaolong-Qwen3-0.6B.i1-Q2_K.gguf) | i1-Q2_K | 0.4 | IQ3_XXS probably better |\n| [GGUF](https://huggingface.co/mradermacher/Xiaolong-Qwen3-0.6B-i1-GGUF/resolve/main/Xiaolong-Qwen3-0.6B.i1-IQ3_XS.gguf) | i1-IQ3_XS | 0.4 |  |\n| [GGUF](https://huggingface.co/mradermacher/Xiaolong-Qwen3-0.6B-i1-GGUF/resolve/main/Xiaolong-Qwen3-0.6B.i1-IQ3_S.gguf) | i1-IQ3_S | 0.4 | beats Q3_K* |\n| [GGUF](https://huggingface.co/mradermacher/Xiaolong-Qwen3-0.6B-i1-GGUF/resolve/main/Xiaolong-Qwen3-0.6B.i1-Q3_K_S.gguf) | i1-Q3_K_S | 0.4 | IQ3_XS probably better |\n| [GGUF](https://huggingface.co/mradermacher/Xiaolong-Qwen3-0.6B-i1-GGUF/resolve/main/Xiaolong-Qwen3-0.6B.i1-IQ3_M.gguf) | i1-IQ3_M | 0.4 |  |\n| [GGUF](https://huggingface.co/mradermacher/Xiaolong-Qwen3-0.6B-i1-GGUF/resolve/main/Xiaolong-Qwen3-0.6B.i1-Q3_K_M.gguf) | i1-Q3_K_M | 0.4 | IQ3_S probably better |\n| [GGUF](https://huggingface.co/mradermacher/Xiaolong-Qwen3-0.6B-i1-GGUF/resolve/main/Xiaolong-Qwen3-0.6B.i1-IQ4_XS.gguf) | i1-IQ4_XS | 0.5 |  |\n| [GGUF](https://huggingface.co/mradermacher/Xiaolong-Qwen3-0.6B-i1-GGUF/resolve/main/Xiaolong-Qwen3-0.6B.i1-Q3_K_L.gguf) | i1-Q3_K_L | 0.5 | IQ3_M probably better |\n| [GGUF](https://huggingface.co/mradermacher/Xiaolong-Qwen3-0.6B-i1-GGUF/resolve/main/Xiaolong-Qwen3-0.6B.i1-IQ4_NL.gguf) | i1-IQ4_NL | 0.5 | prefer IQ4_XS |\n| [GGUF](https://huggingface.co/mradermacher/Xiaolong-Qwen3-0.6B-i1-GGUF/resolve/main/Xiaolong-Qwen3-0.6B.i1-Q4_0.gguf) | i1-Q4_0 | 0.5 | fast, low quality |\n| [GGUF](https://huggingface.co/mradermacher/Xiaolong-Qwen3-0.6B-i1-GGUF/resolve/main/Xiaolong-Qwen3-0.6B.i1-Q4_K_S.gguf) | i1-Q4_K_S | 0.5 | optimal size/speed/quality |\n| [GGUF](https://huggingface.co/mradermacher/Xiaolong-Qwen3-0.6B-i1-GGUF/resolve/main/Xiaolong-Qwen3-0.6B.i1-Q4_K_M.gguf) | i1-Q4_K_M | 0.5 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/Xiaolong-Qwen3-0.6B-i1-GGUF/resolve/main/Xiaolong-Qwen3-0.6B.i1-Q4_1.gguf) | i1-Q4_1 | 0.5 |  |\n| [GGUF](https://huggingface.co/mradermacher/Xiaolong-Qwen3-0.6B-i1-GGUF/resolve/main/Xiaolong-Qwen3-0.6B.i1-Q5_K_S.gguf) | i1-Q5_K_S | 0.5 |  |\n| [GGUF](https://huggingface.co/mradermacher/Xiaolong-Qwen3-0.6B-i1-GGUF/resolve/main/Xiaolong-Qwen3-0.6B.i1-Q5_K_M.gguf) | i1-Q5_K_M | 0.5 |  |\n| [GGUF](https://huggingface.co/mradermacher/Xiaolong-Qwen3-0.6B-i1-GGUF/resolve/main/Xiaolong-Qwen3-0.6B.i1-Q6_K.gguf) | i1-Q6_K | 0.6 | practically like static Q6_K |\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. Additional thanks to [@nicoboss](https://huggingface.co/nicoboss) for giving me access to his private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to.\n\n<!-- end -->\n",
    "related_quantizations": []
  },
  "tags": [
    "transformers",
    "gguf",
    "orpo",
    "uncensored",
    "reasoning",
    "cot",
    "en",
    "dataset:nbeerbower/GreatFirewall-DPO",
    "dataset:nbeerbower/Schule-DPO",
    "dataset:nbeerbower/Purpura-DPO",
    "dataset:nbeerbower/Arkhaios-DPO",
    "dataset:jondurbin/truthy-dpo-v0.1",
    "dataset:antiven0m/physical-reasoning-dpo",
    "dataset:flammenai/Date-DPO-NoAsterisks",
    "dataset:flammenai/Prude-Phi3-DPO",
    "dataset:Atsunori/HelpSteer2-DPO",
    "dataset:jondurbin/gutenberg-dpo-v0.1",
    "dataset:nbeerbower/gutenberg2-dpo",
    "dataset:nbeerbower/gutenberg-moderne-dpo",
    "dataset:GeneralReasoning/GeneralThought-430K",
    "dataset:nvidia/OpenMathReasoning",
    "dataset:nvidia/OpenCodeReasoning",
    "base_model:nbeerbower/Xiaolong-Qwen3-0.6B",
    "base_model:quantized:nbeerbower/Xiaolong-Qwen3-0.6B",
    "license:apache-2.0",
    "endpoints_compatible",
    "region:us",
    "imatrix",
    "conversational"
  ],
  "likes": 0,
  "downloads": 135,
  "gated": false,
  "private": false,
  "last_modified": "2025-07-11T03:25:34.000Z",
  "created_at": "2025-05-06T21:16:12.000Z",
  "pipeline_tag": "",
  "library_name": "transformers"
}

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