mradermacher/alia-40b-i1-gguf overview

{
  "metadata": {},
  "card_data": {
    "base_model": "BSC-LT/ALIA-40b",
    "datasets": [
      "oscar-corpus/colossal-oscar-1.0",
      "HuggingFaceFW/fineweb-edu",
      "joelniklaus/eurlex_resources",
      "joelniklaus/legal-mc4",
      "projecte-aina/CATalog",
      "UFRGS/brwac",
      "community-datasets/hrwac",
      "danish-foundation-models/danish-gigaword",
      "HiTZ/euscrawl",
      "PleIAs/French-PD-Newspapers",
      "PleIAs/French-PD-Books",
      "AI-team-UoA/greek_legal_code",
      "HiTZ/latxa-corpus-v1.1",
      "allenai/peS2o",
      "pile-of-law/pile-of-law",
      "PORTULAN/parlamento-pt",
      "hoskinson-center/proof-pile",
      "togethercomputer/RedPajama-Data-1T",
      "bigcode/starcoderdata",
      "bjoernp/tagesschau-2018-2023",
      "EleutherAI/the_pile_deduplicated"
    ],
    "language": [
      "bg",
      "ca",
      "code",
      "cs",
      "cy",
      "da",
      "de",
      "el",
      "en",
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      "sr",
      "sv",
      "uk"
    ],
    "library_name": "transformers",
    "license": "apache-2.0",
    "quantized_by": "mradermacher",
    "frontmatter": {
      "base_model": "BSC-LT/ALIA-40b",
      "datasets": [
        "oscar-corpus/colossal-oscar-1.0",
        "HuggingFaceFW/fineweb-edu",
        "joelniklaus/eurlex_resources",
        "joelniklaus/legal-mc4",
        "projecte-aina/CATalog",
        "UFRGS/brwac",
        "community-datasets/hrwac",
        "danish-foundation-models/danish-gigaword",
        "HiTZ/euscrawl",
        "PleIAs/French-PD-Newspapers",
        "PleIAs/French-PD-Books",
        "AI-team-UoA/greek_legal_code",
        "HiTZ/latxa-corpus-v1.1",
        "allenai/peS2o",
        "pile-of-law/pile-of-law",
        "PORTULAN/parlamento-pt",
        "hoskinson-center/proof-pile",
        "togethercomputer/RedPajama-Data-1T",
        "bigcode/starcoderdata",
        "bjoernp/tagesschau-2018-2023",
        "EleutherAI/the_pile_deduplicated"
      ],
      "language": [
        "bg",
        "ca",
        "code",
        "cs",
        "cy",
        "da",
        "de",
        "el",
        "en",
        "es",
        "et",
        "eu",
        "fi",
        "fr",
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        "hu",
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        "pl",
        "pt",
        "ro",
        "ru",
        "sh",
        "sk",
        "sl",
        "sr",
        "sv",
        "uk"
      ],
      "library_name": "transformers",
      "license": "apache-2.0",
      "quantized_by": "mradermacher"
    },
    "hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
    "summary": "## About      weighted/imatrix quants of https://huggingface.co/BSC-LT/ALIA-40b  static quants are available at https://huggingface.co/mradermacher/ALIA-40b-GGUF",
    "quick_links": [],
    "benchmark_table_html": "",
    "readme_markdown": "---\nbase_model: BSC-LT/ALIA-40b\ndatasets:\n- oscar-corpus/colossal-oscar-1.0\n- HuggingFaceFW/fineweb-edu\n- joelniklaus/eurlex_resources\n- joelniklaus/legal-mc4\n- projecte-aina/CATalog\n- UFRGS/brwac\n- community-datasets/hrwac\n- danish-foundation-models/danish-gigaword\n- HiTZ/euscrawl\n- PleIAs/French-PD-Newspapers\n- PleIAs/French-PD-Books\n- AI-team-UoA/greek_legal_code\n- HiTZ/latxa-corpus-v1.1\n- allenai/peS2o\n- pile-of-law/pile-of-law\n- PORTULAN/parlamento-pt\n- hoskinson-center/proof-pile\n- togethercomputer/RedPajama-Data-1T\n- bigcode/starcoderdata\n- bjoernp/tagesschau-2018-2023\n- EleutherAI/the_pile_deduplicated\nlanguage:\n- bg\n- ca\n- code\n- cs\n- cy\n- da\n- de\n- el\n- en\n- es\n- et\n- eu\n- fi\n- fr\n- ga\n- gl\n- hr\n- hu\n- it\n- lt\n- lv\n- mt\n- nl\n- nn\n- \\no\n- oc\n- pl\n- pt\n- ro\n- ru\n- sh\n- sk\n- sl\n- sr\n- sv\n- uk\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: nicoboss -->\nweighted/imatrix quants of https://huggingface.co/BSC-LT/ALIA-40b\n\n<!-- provided-files -->\nstatic quants are available at https://huggingface.co/mradermacher/ALIA-40b-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/ALIA-40b-i1-GGUF/resolve/main/ALIA-40b.i1-IQ1_S.gguf) | i1-IQ1_S | 9.8 | for the desperate |\n| [GGUF](https://huggingface.co/mradermacher/ALIA-40b-i1-GGUF/resolve/main/ALIA-40b.i1-IQ1_M.gguf) | i1-IQ1_M | 10.6 | mostly desperate |\n| [GGUF](https://huggingface.co/mradermacher/ALIA-40b-i1-GGUF/resolve/main/ALIA-40b.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 11.8 |  |\n| [GGUF](https://huggingface.co/mradermacher/ALIA-40b-i1-GGUF/resolve/main/ALIA-40b.i1-IQ2_XS.gguf) | i1-IQ2_XS | 12.9 |  |\n| [GGUF](https://huggingface.co/mradermacher/ALIA-40b-i1-GGUF/resolve/main/ALIA-40b.i1-IQ2_S.gguf) | i1-IQ2_S | 13.7 |  |\n| [GGUF](https://huggingface.co/mradermacher/ALIA-40b-i1-GGUF/resolve/main/ALIA-40b.i1-IQ2_M.gguf) | i1-IQ2_M | 14.6 |  |\n| [GGUF](https://huggingface.co/mradermacher/ALIA-40b-i1-GGUF/resolve/main/ALIA-40b.i1-Q2_K_S.gguf) | i1-Q2_K_S | 14.8 | very low quality |\n| [GGUF](https://huggingface.co/mradermacher/ALIA-40b-i1-GGUF/resolve/main/ALIA-40b.i1-Q2_K.gguf) | i1-Q2_K | 15.8 | IQ3_XXS probably better |\n| [GGUF](https://huggingface.co/mradermacher/ALIA-40b-i1-GGUF/resolve/main/ALIA-40b.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 16.3 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/ALIA-40b-i1-GGUF/resolve/main/ALIA-40b.i1-IQ3_XS.gguf) | i1-IQ3_XS | 17.5 |  |\n| [GGUF](https://huggingface.co/mradermacher/ALIA-40b-i1-GGUF/resolve/main/ALIA-40b.i1-Q3_K_S.gguf) | i1-Q3_K_S | 18.3 | IQ3_XS probably better |\n| [GGUF](https://huggingface.co/mradermacher/ALIA-40b-i1-GGUF/resolve/main/ALIA-40b.i1-IQ3_S.gguf) | i1-IQ3_S | 18.4 | beats Q3_K* |\n| [GGUF](https://huggingface.co/mradermacher/ALIA-40b-i1-GGUF/resolve/main/ALIA-40b.i1-IQ3_M.gguf) | i1-IQ3_M | 18.9 |  |\n| [GGUF](https://huggingface.co/mradermacher/ALIA-40b-i1-GGUF/resolve/main/ALIA-40b.i1-Q3_K_M.gguf) | i1-Q3_K_M | 20.1 | IQ3_S probably better |\n| [GGUF](https://huggingface.co/mradermacher/ALIA-40b-i1-GGUF/resolve/main/ALIA-40b.i1-Q3_K_L.gguf) | i1-Q3_K_L | 21.7 | IQ3_M probably better |\n| [GGUF](https://huggingface.co/mradermacher/ALIA-40b-i1-GGUF/resolve/main/ALIA-40b.i1-IQ4_XS.gguf) | i1-IQ4_XS | 22.3 |  |\n| [GGUF](https://huggingface.co/mradermacher/ALIA-40b-i1-GGUF/resolve/main/ALIA-40b.i1-Q4_0.gguf) | i1-Q4_0 | 23.5 | fast, low quality |\n| [GGUF](https://huggingface.co/mradermacher/ALIA-40b-i1-GGUF/resolve/main/ALIA-40b.i1-Q4_K_S.gguf) | i1-Q4_K_S | 23.5 | optimal size/speed/quality |\n| [GGUF](https://huggingface.co/mradermacher/ALIA-40b-i1-GGUF/resolve/main/ALIA-40b.i1-Q4_K_M.gguf) | i1-Q4_K_M | 24.7 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/ALIA-40b-i1-GGUF/resolve/main/ALIA-40b.i1-Q4_1.gguf) | i1-Q4_1 | 25.8 |  |\n| [GGUF](https://huggingface.co/mradermacher/ALIA-40b-i1-GGUF/resolve/main/ALIA-40b.i1-Q5_K_S.gguf) | i1-Q5_K_S | 28.2 |  |\n| [GGUF](https://huggingface.co/mradermacher/ALIA-40b-i1-GGUF/resolve/main/ALIA-40b.i1-Q5_K_M.gguf) | i1-Q5_K_M | 28.9 |  |\n| [GGUF](https://huggingface.co/mradermacher/ALIA-40b-i1-GGUF/resolve/main/ALIA-40b.i1-Q6_K.gguf) | i1-Q6_K | 33.3 | 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": [
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    "gguf",
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    "ca",
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    "mt",
    "nl",
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    "oc",
    "pl",
    "pt",
    "ro",
    "ru",
    "sh",
    "sk",
    "sl",
    "sr",
    "sv",
    "uk",
    "dataset:oscar-corpus/colossal-oscar-1.0",
    "dataset:HuggingFaceFW/fineweb-edu",
    "dataset:joelniklaus/eurlex_resources",
    "dataset:joelniklaus/legal-mc4",
    "dataset:projecte-aina/CATalog",
    "dataset:UFRGS/brwac",
    "dataset:community-datasets/hrwac",
    "dataset:danish-foundation-models/danish-gigaword",
    "dataset:HiTZ/euscrawl",
    "dataset:PleIAs/French-PD-Newspapers",
    "dataset:PleIAs/French-PD-Books",
    "dataset:AI-team-UoA/greek_legal_code",
    "dataset:HiTZ/latxa-corpus-v1.1",
    "dataset:allenai/peS2o",
    "dataset:pile-of-law/pile-of-law",
    "dataset:PORTULAN/parlamento-pt",
    "dataset:hoskinson-center/proof-pile",
    "dataset:togethercomputer/RedPajama-Data-1T",
    "dataset:bigcode/starcoderdata",
    "dataset:bjoernp/tagesschau-2018-2023",
    "dataset:EleutherAI/the_pile_deduplicated",
    "base_model:BSC-LT/ALIA-40b",
    "base_model:quantized:BSC-LT/ALIA-40b",
    "license:apache-2.0",
    "endpoints_compatible",
    "region:us",
    "imatrix"
  ],
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  "created_at": "2025-01-22T15:30:04.000Z",
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