mradermacher/eurollm-22b-instruct-2512-gguf overview

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    "library_name": "transformers",
    "license": "apache-2.0",
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    "quantized_by": "mradermacher",
    "frontmatter": {
      "base_model": "utter-project/EuroLLM-22B-Instruct-2512",
      "language": [
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    "hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
    "summary": "## About         static quants of https://huggingface.co/utter-project/EuroLLM-22B-Instruct-2512  ***For a convenient overview and download list, visit our model page for this model.*** weighted/imatrix quants are available at https://huggingface.co/mradermacher/EuroLLM-22B-Instruct-2512-i1-GGUF",
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    "readme_markdown": "---\nbase_model: utter-project/EuroLLM-22B-Instruct-2512\nlanguage:\n- en\n- de\n- es\n- fr\n- it\n- pt\n- pl\n- nl\n- tr\n- sv\n- cs\n- el\n- hu\n- ro\n- fi\n- uk\n- sl\n- sk\n- da\n- lt\n- lv\n- et\n- bg\n- no\n- ca\n- hr\n- ga\n- mt\n- gl\n- zh\n- ru\n- ko\n- ja\n- ar\n- hi\nlibrary_name: transformers\nlicense: apache-2.0\nmradermacher:\n  readme_rev: 1\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:  -->\n<!-- ### quants:  x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->\n<!-- ### quants_skip:  -->\n<!-- ### skip_mmproj:  -->\nstatic quants of https://huggingface.co/utter-project/EuroLLM-22B-Instruct-2512\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#EuroLLM-22B-Instruct-2512-GGUF).***\n\nweighted/imatrix quants are available at https://huggingface.co/mradermacher/EuroLLM-22B-Instruct-2512-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/EuroLLM-22B-Instruct-2512-GGUF/resolve/main/EuroLLM-22B-Instruct-2512.Q2_K.gguf) | Q2_K | 8.8 |  |\n| [GGUF](https://huggingface.co/mradermacher/EuroLLM-22B-Instruct-2512-GGUF/resolve/main/EuroLLM-22B-Instruct-2512.Q3_K_S.gguf) | Q3_K_S | 10.1 |  |\n| [GGUF](https://huggingface.co/mradermacher/EuroLLM-22B-Instruct-2512-GGUF/resolve/main/EuroLLM-22B-Instruct-2512.Q3_K_M.gguf) | Q3_K_M | 11.2 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/EuroLLM-22B-Instruct-2512-GGUF/resolve/main/EuroLLM-22B-Instruct-2512.Q3_K_L.gguf) | Q3_K_L | 12.2 |  |\n| [GGUF](https://huggingface.co/mradermacher/EuroLLM-22B-Instruct-2512-GGUF/resolve/main/EuroLLM-22B-Instruct-2512.IQ4_XS.gguf) | IQ4_XS | 12.5 |  |\n| [GGUF](https://huggingface.co/mradermacher/EuroLLM-22B-Instruct-2512-GGUF/resolve/main/EuroLLM-22B-Instruct-2512.Q4_K_S.gguf) | Q4_K_S | 13.1 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/EuroLLM-22B-Instruct-2512-GGUF/resolve/main/EuroLLM-22B-Instruct-2512.Q4_K_M.gguf) | Q4_K_M | 13.8 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/EuroLLM-22B-Instruct-2512-GGUF/resolve/main/EuroLLM-22B-Instruct-2512.Q5_K_S.gguf) | Q5_K_S | 15.8 |  |\n| [GGUF](https://huggingface.co/mradermacher/EuroLLM-22B-Instruct-2512-GGUF/resolve/main/EuroLLM-22B-Instruct-2512.Q5_K_M.gguf) | Q5_K_M | 16.1 |  |\n| [GGUF](https://huggingface.co/mradermacher/EuroLLM-22B-Instruct-2512-GGUF/resolve/main/EuroLLM-22B-Instruct-2512.Q6_K.gguf) | Q6_K | 18.7 | very good quality |\n| [GGUF](https://huggingface.co/mradermacher/EuroLLM-22B-Instruct-2512-GGUF/resolve/main/EuroLLM-22B-Instruct-2512.Q8_0.gguf) | Q8_0 | 24.2 | fast, best quality |\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",
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