mradermacher/mixtral-8x7b-instruct-v0.1-exhaustive-lora-sft-pruned-2-experts-gguf overview

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    "base_model": "Na0s/Mixtral-8x7B-Instruct-v0.1-exhaustive-LoRA-SFT-pruned-2-experts",
    "language": [
      "en"
    ],
    "library_name": "transformers",
    "quantized_by": "mradermacher",
    "tags": [],
    "frontmatter": {
      "base_model": "Na0s/Mixtral-8x7B-Instruct-v0.1-exhaustive-LoRA-SFT-pruned-2-experts",
      "language": [
        "en"
      ],
      "library_name": "transformers",
      "quantized_by": "mradermacher",
      "tags": "[]"
    },
    "hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
    "summary": "## About      static quants of https://huggingface.co/Na0s/Mixtral-8x7B-Instruct-v0.1-exhaustive-LoRA-SFT-pruned-2-experts  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: Na0s/Mixtral-8x7B-Instruct-v0.1-exhaustive-LoRA-SFT-pruned-2-experts\nlanguage:\n- en\nlibrary_name: transformers\nquantized_by: mradermacher\ntags: []\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/Na0s/Mixtral-8x7B-Instruct-v0.1-exhaustive-LoRA-SFT-pruned-2-experts\n\n<!-- provided-files -->\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/Mixtral-8x7B-Instruct-v0.1-exhaustive-LoRA-SFT-pruned-2-experts-GGUF/resolve/main/Mixtral-8x7B-Instruct-v0.1-exhaustive-LoRA-SFT-pruned-2-experts.Q2_K.gguf) | Q2_K | 13.0 |  |\n| [GGUF](https://huggingface.co/mradermacher/Mixtral-8x7B-Instruct-v0.1-exhaustive-LoRA-SFT-pruned-2-experts-GGUF/resolve/main/Mixtral-8x7B-Instruct-v0.1-exhaustive-LoRA-SFT-pruned-2-experts.Q3_K_S.gguf) | Q3_K_S | 15.4 |  |\n| [GGUF](https://huggingface.co/mradermacher/Mixtral-8x7B-Instruct-v0.1-exhaustive-LoRA-SFT-pruned-2-experts-GGUF/resolve/main/Mixtral-8x7B-Instruct-v0.1-exhaustive-LoRA-SFT-pruned-2-experts.Q3_K_M.gguf) | Q3_K_M | 17.1 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/Mixtral-8x7B-Instruct-v0.1-exhaustive-LoRA-SFT-pruned-2-experts-GGUF/resolve/main/Mixtral-8x7B-Instruct-v0.1-exhaustive-LoRA-SFT-pruned-2-experts.Q3_K_L.gguf) | Q3_K_L | 18.5 |  |\n| [GGUF](https://huggingface.co/mradermacher/Mixtral-8x7B-Instruct-v0.1-exhaustive-LoRA-SFT-pruned-2-experts-GGUF/resolve/main/Mixtral-8x7B-Instruct-v0.1-exhaustive-LoRA-SFT-pruned-2-experts.IQ4_XS.gguf) | IQ4_XS | 19.2 |  |\n| [GGUF](https://huggingface.co/mradermacher/Mixtral-8x7B-Instruct-v0.1-exhaustive-LoRA-SFT-pruned-2-experts-GGUF/resolve/main/Mixtral-8x7B-Instruct-v0.1-exhaustive-LoRA-SFT-pruned-2-experts.Q4_K_S.gguf) | Q4_K_S | 20.2 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/Mixtral-8x7B-Instruct-v0.1-exhaustive-LoRA-SFT-pruned-2-experts-GGUF/resolve/main/Mixtral-8x7B-Instruct-v0.1-exhaustive-LoRA-SFT-pruned-2-experts.Q4_K_M.gguf) | Q4_K_M | 21.5 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/Mixtral-8x7B-Instruct-v0.1-exhaustive-LoRA-SFT-pruned-2-experts-GGUF/resolve/main/Mixtral-8x7B-Instruct-v0.1-exhaustive-LoRA-SFT-pruned-2-experts.Q5_K_S.gguf) | Q5_K_S | 24.5 |  |\n| [GGUF](https://huggingface.co/mradermacher/Mixtral-8x7B-Instruct-v0.1-exhaustive-LoRA-SFT-pruned-2-experts-GGUF/resolve/main/Mixtral-8x7B-Instruct-v0.1-exhaustive-LoRA-SFT-pruned-2-experts.Q5_K_M.gguf) | Q5_K_M | 25.2 |  |\n| [GGUF](https://huggingface.co/mradermacher/Mixtral-8x7B-Instruct-v0.1-exhaustive-LoRA-SFT-pruned-2-experts-GGUF/resolve/main/Mixtral-8x7B-Instruct-v0.1-exhaustive-LoRA-SFT-pruned-2-experts.Q6_K.gguf) | Q6_K | 29.2 | very good quality |\n| [GGUF](https://huggingface.co/mradermacher/Mixtral-8x7B-Instruct-v0.1-exhaustive-LoRA-SFT-pruned-2-experts-GGUF/resolve/main/Mixtral-8x7B-Instruct-v0.1-exhaustive-LoRA-SFT-pruned-2-experts.Q8_0.gguf) | Q8_0 | 37.7 | 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",
    "related_quantizations": []
  },
  "tags": [
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    "gguf",
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    "base_model:Na0s/Mixtral-8x7B-Instruct-v0.1-exhaustive-LoRA-SFT-pruned-2-experts",
    "base_model:quantized:Na0s/Mixtral-8x7B-Instruct-v0.1-exhaustive-LoRA-SFT-pruned-2-experts",
    "endpoints_compatible",
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    "conversational"
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  "last_modified": "2024-11-19T05:53:11.000Z",
  "created_at": "2024-11-19T04:21:40.000Z",
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  "library_name": "transformers"
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