mradermacher/adelie-dpo-1.5b-gguf overview

{
  "metadata": {},
  "card_data": {
    "base_model": "THU-KEG/ADELIE-DPO-1.5B",
    "datasets": [
      "ACE05",
      "conll2003",
      "conll2012_ontonotesv5",
      "rams",
      "tacred",
      "fewrel",
      "maven"
    ],
    "language": [
      "en"
    ],
    "library_name": "transformers",
    "mradermacher": {
      "readme_rev": 1
    },
    "quantized_by": "mradermacher",
    "tags": [
      "text-generation-inference",
      "Information Extraction",
      "IE",
      "Named Entity Recogniton",
      "Event Extraction",
      "Relation Extraction",
      "LLaMA"
    ],
    "frontmatter": {
      "base_model": "THU-KEG/ADELIE-DPO-1.5B",
      "datasets": [
        "ACE05",
        "conll2003",
        "conll2012_ontonotesv5",
        "rams",
        "tacred",
        "fewrel",
        "maven"
      ],
      "language": [
        "en"
      ],
      "library_name": "transformers",
      "mradermacher": [],
      "quantized_by": "mradermacher",
      "tags": [
        "text-generation-inference",
        "Information Extraction",
        "IE",
        "Named Entity Recogniton",
        "Event Extraction",
        "Relation Extraction",
        "LLaMA"
      ]
    },
    "hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
    "summary": "## About      static quants of https://huggingface.co/THU-KEG/ADELIE-DPO-1.5B  ***For a convenient overview and download list, visit our model page for this model.*** weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.",
    "quick_links": [],
    "benchmark_table_html": "",
    "readme_markdown": "---\nbase_model: THU-KEG/ADELIE-DPO-1.5B\ndatasets:\n- ACE05\n- conll2003\n- conll2012_ontonotesv5\n- rams\n- tacred\n- fewrel\n- maven\nlanguage:\n- en\nlibrary_name: transformers\nmradermacher:\n  readme_rev: 1\nquantized_by: mradermacher\ntags:\n- text-generation-inference\n- Information Extraction\n- IE\n- Named Entity Recogniton\n- Event Extraction\n- Relation Extraction\n- LLaMA\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/THU-KEG/ADELIE-DPO-1.5B\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#ADELIE-DPO-1.5B-GGUF).***\n\nweighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.\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/ADELIE-DPO-1.5B-GGUF/resolve/main/ADELIE-DPO-1.5B.Q2_K.gguf) | Q2_K | 0.9 |  |\n| [GGUF](https://huggingface.co/mradermacher/ADELIE-DPO-1.5B-GGUF/resolve/main/ADELIE-DPO-1.5B.Q3_K_S.gguf) | Q3_K_S | 1.0 |  |\n| [GGUF](https://huggingface.co/mradermacher/ADELIE-DPO-1.5B-GGUF/resolve/main/ADELIE-DPO-1.5B.Q3_K_M.gguf) | Q3_K_M | 1.0 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/ADELIE-DPO-1.5B-GGUF/resolve/main/ADELIE-DPO-1.5B.Q3_K_L.gguf) | Q3_K_L | 1.1 |  |\n| [GGUF](https://huggingface.co/mradermacher/ADELIE-DPO-1.5B-GGUF/resolve/main/ADELIE-DPO-1.5B.IQ4_XS.gguf) | IQ4_XS | 1.1 |  |\n| [GGUF](https://huggingface.co/mradermacher/ADELIE-DPO-1.5B-GGUF/resolve/main/ADELIE-DPO-1.5B.Q4_K_S.gguf) | Q4_K_S | 1.2 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/ADELIE-DPO-1.5B-GGUF/resolve/main/ADELIE-DPO-1.5B.Q4_K_M.gguf) | Q4_K_M | 1.2 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/ADELIE-DPO-1.5B-GGUF/resolve/main/ADELIE-DPO-1.5B.Q5_K_S.gguf) | Q5_K_S | 1.4 |  |\n| [GGUF](https://huggingface.co/mradermacher/ADELIE-DPO-1.5B-GGUF/resolve/main/ADELIE-DPO-1.5B.Q5_K_M.gguf) | Q5_K_M | 1.4 |  |\n| [GGUF](https://huggingface.co/mradermacher/ADELIE-DPO-1.5B-GGUF/resolve/main/ADELIE-DPO-1.5B.Q6_K.gguf) | Q6_K | 1.6 | very good quality |\n| [GGUF](https://huggingface.co/mradermacher/ADELIE-DPO-1.5B-GGUF/resolve/main/ADELIE-DPO-1.5B.Q8_0.gguf) | Q8_0 | 2.0 | fast, best quality |\n| [GGUF](https://huggingface.co/mradermacher/ADELIE-DPO-1.5B-GGUF/resolve/main/ADELIE-DPO-1.5B.f16.gguf) | f16 | 3.7 | 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",
    "text-generation-inference",
    "Information Extraction",
    "IE",
    "Named Entity Recogniton",
    "Event Extraction",
    "Relation Extraction",
    "LLaMA",
    "en",
    "dataset:ACE05",
    "dataset:conll2003",
    "dataset:conll2012_ontonotesv5",
    "dataset:rams",
    "dataset:tacred",
    "dataset:fewrel",
    "dataset:maven",
    "base_model:THU-KEG/ADELIE-DPO-1.5B",
    "base_model:quantized:THU-KEG/ADELIE-DPO-1.5B",
    "endpoints_compatible",
    "region:us",
    "conversational"
  ],
  "likes": 1,
  "downloads": 122,
  "gated": false,
  "private": false,
  "last_modified": "2025-07-11T06:35:18.000Z",
  "created_at": "2025-04-06T12:51:25.000Z",
  "pipeline_tag": "",
  "library_name": "transformers"
}

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  "createdAt": "2025-04-06T12:51:25.000Z",
  "lastModified": "2025-07-11T06:35:18.000Z",
  "author": "mradermacher",
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