mradermacher/apollo2-3.8b-i1-gguf overview

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    "base_model": "FreedomIntelligence/Apollo2-3.8B",
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    "tags": [
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    "frontmatter": {
      "base_model": "FreedomIntelligence/Apollo2-3.8B",
      "datasets": [
        "FreedomIntelligence/ApolloMoEDataset"
      ],
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      "license": "apache-2.0",
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    "hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
    "summary": "## About      weighted/imatrix quants of https://huggingface.co/FreedomIntelligence/Apollo2-3.8B  static quants are available at https://huggingface.co/mradermacher/Apollo2-3.8B-GGUF",
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    "readme_markdown": "---\nbase_model: FreedomIntelligence/Apollo2-3.8B\ndatasets:\n- FreedomIntelligence/ApolloMoEDataset\nlanguage:\n- ar\n- en\n- zh\n- ko\n- ja\n- mn\n- th\n- vi\n- lo\n- mg\n- de\n- pt\n- es\n- fr\n- ru\n- it\n- hr\n- gl\n- cs\n- co\n- la\n- uk\n- bs\n- bg\n- eo\n- sq\n- da\n- sa\n- gn\n- sr\n- sk\n- gd\n- lb\n- hi\n- ku\n- mt\n- he\n- ln\n- bm\n- sw\n- ig\n- rw\n- ha\nlibrary_name: transformers\nlicense: apache-2.0\nquantized_by: mradermacher\ntags:\n- biology\n- medical\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/FreedomIntelligence/Apollo2-3.8B\n\n<!-- provided-files -->\nstatic quants are available at https://huggingface.co/mradermacher/Apollo2-3.8B-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/Apollo2-3.8B-i1-GGUF/resolve/main/Apollo2-3.8B.i1-IQ1_S.gguf) | i1-IQ1_S | 0.9 | for the desperate |\n| [GGUF](https://huggingface.co/mradermacher/Apollo2-3.8B-i1-GGUF/resolve/main/Apollo2-3.8B.i1-IQ1_M.gguf) | i1-IQ1_M | 1.0 | mostly desperate |\n| [GGUF](https://huggingface.co/mradermacher/Apollo2-3.8B-i1-GGUF/resolve/main/Apollo2-3.8B.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 1.1 |  |\n| [GGUF](https://huggingface.co/mradermacher/Apollo2-3.8B-i1-GGUF/resolve/main/Apollo2-3.8B.i1-IQ2_XS.gguf) | i1-IQ2_XS | 1.3 |  |\n| [GGUF](https://huggingface.co/mradermacher/Apollo2-3.8B-i1-GGUF/resolve/main/Apollo2-3.8B.i1-IQ2_S.gguf) | i1-IQ2_S | 1.3 |  |\n| [GGUF](https://huggingface.co/mradermacher/Apollo2-3.8B-i1-GGUF/resolve/main/Apollo2-3.8B.i1-IQ2_M.gguf) | i1-IQ2_M | 1.4 |  |\n| [GGUF](https://huggingface.co/mradermacher/Apollo2-3.8B-i1-GGUF/resolve/main/Apollo2-3.8B.i1-Q2_K_S.gguf) | i1-Q2_K_S | 1.4 | very low quality |\n| [GGUF](https://huggingface.co/mradermacher/Apollo2-3.8B-i1-GGUF/resolve/main/Apollo2-3.8B.i1-Q2_K.gguf) | i1-Q2_K | 1.5 | IQ3_XXS probably better |\n| [GGUF](https://huggingface.co/mradermacher/Apollo2-3.8B-i1-GGUF/resolve/main/Apollo2-3.8B.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 1.6 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/Apollo2-3.8B-i1-GGUF/resolve/main/Apollo2-3.8B.i1-IQ3_XS.gguf) | i1-IQ3_XS | 1.7 |  |\n| [GGUF](https://huggingface.co/mradermacher/Apollo2-3.8B-i1-GGUF/resolve/main/Apollo2-3.8B.i1-IQ3_S.gguf) | i1-IQ3_S | 1.8 | beats Q3_K* |\n| [GGUF](https://huggingface.co/mradermacher/Apollo2-3.8B-i1-GGUF/resolve/main/Apollo2-3.8B.i1-Q3_K_S.gguf) | i1-Q3_K_S | 1.8 | IQ3_XS probably better |\n| [GGUF](https://huggingface.co/mradermacher/Apollo2-3.8B-i1-GGUF/resolve/main/Apollo2-3.8B.i1-IQ3_M.gguf) | i1-IQ3_M | 2.0 |  |\n| [GGUF](https://huggingface.co/mradermacher/Apollo2-3.8B-i1-GGUF/resolve/main/Apollo2-3.8B.i1-Q3_K_M.gguf) | i1-Q3_K_M | 2.1 | IQ3_S probably better |\n| [GGUF](https://huggingface.co/mradermacher/Apollo2-3.8B-i1-GGUF/resolve/main/Apollo2-3.8B.i1-IQ4_XS.gguf) | i1-IQ4_XS | 2.2 |  |\n| [GGUF](https://huggingface.co/mradermacher/Apollo2-3.8B-i1-GGUF/resolve/main/Apollo2-3.8B.i1-Q3_K_L.gguf) | i1-Q3_K_L | 2.2 | IQ3_M probably better |\n| [GGUF](https://huggingface.co/mradermacher/Apollo2-3.8B-i1-GGUF/resolve/main/Apollo2-3.8B.i1-IQ4_NL.gguf) | i1-IQ4_NL | 2.3 | prefer IQ4_XS |\n| [GGUF](https://huggingface.co/mradermacher/Apollo2-3.8B-i1-GGUF/resolve/main/Apollo2-3.8B.i1-Q4_0.gguf) | i1-Q4_0 | 2.3 | fast, low quality |\n| [GGUF](https://huggingface.co/mradermacher/Apollo2-3.8B-i1-GGUF/resolve/main/Apollo2-3.8B.i1-Q4_K_S.gguf) | i1-Q4_K_S | 2.3 | optimal size/speed/quality |\n| [GGUF](https://huggingface.co/mradermacher/Apollo2-3.8B-i1-GGUF/resolve/main/Apollo2-3.8B.i1-Q4_K_M.gguf) | i1-Q4_K_M | 2.5 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/Apollo2-3.8B-i1-GGUF/resolve/main/Apollo2-3.8B.i1-Q4_1.gguf) | i1-Q4_1 | 2.5 |  |\n| [GGUF](https://huggingface.co/mradermacher/Apollo2-3.8B-i1-GGUF/resolve/main/Apollo2-3.8B.i1-Q5_K_S.gguf) | i1-Q5_K_S | 2.7 |  |\n| [GGUF](https://huggingface.co/mradermacher/Apollo2-3.8B-i1-GGUF/resolve/main/Apollo2-3.8B.i1-Q5_K_M.gguf) | i1-Q5_K_M | 2.9 |  |\n| [GGUF](https://huggingface.co/mradermacher/Apollo2-3.8B-i1-GGUF/resolve/main/Apollo2-3.8B.i1-Q6_K.gguf) | i1-Q6_K | 3.2 | 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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    "dataset:FreedomIntelligence/ApolloMoEDataset",
    "base_model:FreedomIntelligence/Apollo2-3.8B",
    "base_model:quantized:FreedomIntelligence/Apollo2-3.8B",
    "license:apache-2.0",
    "endpoints_compatible",
    "region:us",
    "imatrix",
    "conversational"
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  "last_modified": "2025-01-24T12:47:55.000Z",
  "created_at": "2025-01-24T12:11:37.000Z",
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