mradermacher/pythia-2.8b-tldr-iterative-sampo-gguf overview

{
  "metadata": {},
  "card_data": {
    "base_model": "jiazhengli/Pythia-2.8B-TLDR-Iterative-SamPO",
    "datasets": [
      "webis/tldr-17"
    ],
    "language": [
      "en"
    ],
    "library_name": "transformers",
    "license": "apache-2.0",
    "quantized_by": "mradermacher",
    "frontmatter": {
      "base_model": "jiazhengli/Pythia-2.8B-TLDR-Iterative-SamPO",
      "datasets": [
        "webis/tldr-17"
      ],
      "language": [
        "en"
      ],
      "library_name": "transformers",
      "license": "apache-2.0",
      "quantized_by": "mradermacher"
    },
    "hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
    "summary": "## About      static quants of https://huggingface.co/jiazhengli/Pythia-2.8B-TLDR-Iterative-SamPO  weighted/imatrix quants are available at https://huggingface.co/mradermacher/Pythia-2.8B-TLDR-Iterative-SamPO-i1-GGUF",
    "quick_links": [],
    "benchmark_table_html": "",
    "readme_markdown": "---\nbase_model: jiazhengli/Pythia-2.8B-TLDR-Iterative-SamPO\ndatasets:\n- webis/tldr-17\nlanguage:\n- en\nlibrary_name: transformers\nlicense: apache-2.0\nquantized_by: mradermacher\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/jiazhengli/Pythia-2.8B-TLDR-Iterative-SamPO\n\n<!-- provided-files -->\nweighted/imatrix quants are available at https://huggingface.co/mradermacher/Pythia-2.8B-TLDR-Iterative-SamPO-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/Pythia-2.8B-TLDR-Iterative-SamPO-GGUF/resolve/main/Pythia-2.8B-TLDR-Iterative-SamPO.Q2_K.gguf) | Q2_K | 1.2 |  |\n| [GGUF](https://huggingface.co/mradermacher/Pythia-2.8B-TLDR-Iterative-SamPO-GGUF/resolve/main/Pythia-2.8B-TLDR-Iterative-SamPO.Q3_K_S.gguf) | Q3_K_S | 1.3 |  |\n| [GGUF](https://huggingface.co/mradermacher/Pythia-2.8B-TLDR-Iterative-SamPO-GGUF/resolve/main/Pythia-2.8B-TLDR-Iterative-SamPO.Q3_K_M.gguf) | Q3_K_M | 1.6 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/Pythia-2.8B-TLDR-Iterative-SamPO-GGUF/resolve/main/Pythia-2.8B-TLDR-Iterative-SamPO.IQ4_XS.gguf) | IQ4_XS | 1.6 |  |\n| [GGUF](https://huggingface.co/mradermacher/Pythia-2.8B-TLDR-Iterative-SamPO-GGUF/resolve/main/Pythia-2.8B-TLDR-Iterative-SamPO.Q3_K_L.gguf) | Q3_K_L | 1.7 |  |\n| [GGUF](https://huggingface.co/mradermacher/Pythia-2.8B-TLDR-Iterative-SamPO-GGUF/resolve/main/Pythia-2.8B-TLDR-Iterative-SamPO.Q4_K_S.gguf) | Q4_K_S | 1.7 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/Pythia-2.8B-TLDR-Iterative-SamPO-GGUF/resolve/main/Pythia-2.8B-TLDR-Iterative-SamPO.Q4_K_M.gguf) | Q4_K_M | 1.9 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/Pythia-2.8B-TLDR-Iterative-SamPO-GGUF/resolve/main/Pythia-2.8B-TLDR-Iterative-SamPO.Q5_K_S.gguf) | Q5_K_S | 2.0 |  |\n| [GGUF](https://huggingface.co/mradermacher/Pythia-2.8B-TLDR-Iterative-SamPO-GGUF/resolve/main/Pythia-2.8B-TLDR-Iterative-SamPO.Q5_K_M.gguf) | Q5_K_M | 2.2 |  |\n| [GGUF](https://huggingface.co/mradermacher/Pythia-2.8B-TLDR-Iterative-SamPO-GGUF/resolve/main/Pythia-2.8B-TLDR-Iterative-SamPO.Q6_K.gguf) | Q6_K | 2.4 | very good quality |\n| [GGUF](https://huggingface.co/mradermacher/Pythia-2.8B-TLDR-Iterative-SamPO-GGUF/resolve/main/Pythia-2.8B-TLDR-Iterative-SamPO.Q8_0.gguf) | Q8_0 | 3.1 | fast, best quality |\n| [GGUF](https://huggingface.co/mradermacher/Pythia-2.8B-TLDR-Iterative-SamPO-GGUF/resolve/main/Pythia-2.8B-TLDR-Iterative-SamPO.f16.gguf) | f16 | 5.7 | 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",
    "en",
    "dataset:webis/tldr-17",
    "base_model:jiazhengli/Pythia-2.8B-TLDR-Iterative-SamPO",
    "base_model:quantized:jiazhengli/Pythia-2.8B-TLDR-Iterative-SamPO",
    "license:apache-2.0",
    "endpoints_compatible",
    "region:us"
  ],
  "likes": 0,
  "downloads": 95,
  "gated": false,
  "private": false,
  "last_modified": "2025-01-26T09:26:44.000Z",
  "created_at": "2024-12-29T15:12:46.000Z",
  "pipeline_tag": "",
  "library_name": "transformers"
}

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  "createdAt": "2024-12-29T15:12:46.000Z",
  "lastModified": "2025-01-26T09:26:44.000Z",
  "author": "mradermacher",
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