mradermacher/einstein-v4-qwen-1.5-32b-i1-gguf overview

{
  "metadata": {},
  "card_data": {
    "base_model": "Weyaxi/Einstein-v4-Qwen-1.5-32B",
    "datasets": [
      "allenai/ai2_arc",
      "camel-ai/physics",
      "camel-ai/chemistry",
      "camel-ai/biology",
      "camel-ai/math",
      "metaeval/reclor",
      "openbookqa",
      "mandyyyyii/scibench",
      "derek-thomas/ScienceQA",
      "TIGER-Lab/ScienceEval",
      "jondurbin/airoboros-3.2",
      "LDJnr/Capybara",
      "Cot-Alpaca-GPT4-From-OpenHermes-2.5",
      "STEM-AI-mtl/Electrical-engineering",
      "knowrohit07/saraswati-stem",
      "sablo/oasst2_curated",
      "glaiveai/glaive-code-assistant",
      "lmsys/lmsys-chat-1m",
      "TIGER-Lab/MathInstruct",
      "bigbio/med_qa",
      "meta-math/MetaMathQA-40K",
      "openbookqa",
      "piqa",
      "metaeval/reclor",
      "derek-thomas/ScienceQA",
      "scibench",
      "sciq",
      "Open-Orca/SlimOrca",
      "migtissera/Synthia-v1.3",
      "TIGER-Lab/ScienceEval"
    ],
    "language": [
      "en"
    ],
    "library_name": "transformers",
    "license": "other",
    "quantized_by": "mradermacher",
    "tags": [
      "axolotl",
      "generated_from_trainer",
      "phi",
      "phi2",
      "einstein",
      "instruct",
      "finetune",
      "chatml",
      "gpt4",
      "synthetic data",
      "science",
      "physics",
      "chemistry",
      "biology",
      "math"
    ],
    "frontmatter": {
      "base_model": "Weyaxi/Einstein-v4-Qwen-1.5-32B",
      "datasets": [
        "allenai/ai2_arc",
        "camel-ai/physics",
        "camel-ai/chemistry",
        "camel-ai/biology",
        "camel-ai/math",
        "metaeval/reclor",
        "openbookqa",
        "mandyyyyii/scibench",
        "derek-thomas/ScienceQA",
        "TIGER-Lab/ScienceEval",
        "jondurbin/airoboros-3.2",
        "LDJnr/Capybara",
        "Cot-Alpaca-GPT4-From-OpenHermes-2.5",
        "STEM-AI-mtl/Electrical-engineering",
        "knowrohit07/saraswati-stem",
        "sablo/oasst2_curated",
        "glaiveai/glaive-code-assistant",
        "lmsys/lmsys-chat-1m",
        "TIGER-Lab/MathInstruct",
        "bigbio/med_qa",
        "meta-math/MetaMathQA-40K",
        "openbookqa",
        "piqa",
        "metaeval/reclor",
        "derek-thomas/ScienceQA",
        "scibench",
        "sciq",
        "Open-Orca/SlimOrca",
        "migtissera/Synthia-v1.3",
        "TIGER-Lab/ScienceEval"
      ],
      "language": [
        "en"
      ],
      "library_name": "transformers",
      "license": "other",
      "quantized_by": "mradermacher",
      "tags": [
        "axolotl",
        "generated_from_trainer",
        "phi",
        "phi2",
        "einstein",
        "instruct",
        "finetune",
        "chatml",
        "gpt4",
        "synthetic data",
        "science",
        "physics",
        "chemistry",
        "biology",
        "math"
      ]
    },
    "hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
    "summary": "## About      weighted/imatrix quants of https://huggingface.co/Weyaxi/Einstein-v4-Qwen-1.5-32B  static quants are available at https://huggingface.co/mradermacher/Einstein-v4-Qwen-1.5-32B-GGUF",
    "quick_links": [],
    "benchmark_table_html": "",
    "readme_markdown": "---\nbase_model: Weyaxi/Einstein-v4-Qwen-1.5-32B\ndatasets:\n- allenai/ai2_arc\n- camel-ai/physics\n- camel-ai/chemistry\n- camel-ai/biology\n- camel-ai/math\n- metaeval/reclor\n- openbookqa\n- mandyyyyii/scibench\n- derek-thomas/ScienceQA\n- TIGER-Lab/ScienceEval\n- jondurbin/airoboros-3.2\n- LDJnr/Capybara\n- Cot-Alpaca-GPT4-From-OpenHermes-2.5\n- STEM-AI-mtl/Electrical-engineering\n- knowrohit07/saraswati-stem\n- sablo/oasst2_curated\n- glaiveai/glaive-code-assistant\n- lmsys/lmsys-chat-1m\n- TIGER-Lab/MathInstruct\n- bigbio/med_qa\n- meta-math/MetaMathQA-40K\n- openbookqa\n- piqa\n- metaeval/reclor\n- derek-thomas/ScienceQA\n- scibench\n- sciq\n- Open-Orca/SlimOrca\n- migtissera/Synthia-v1.3\n- TIGER-Lab/ScienceEval\nlanguage:\n- en\nlibrary_name: transformers\nlicense: other\nquantized_by: mradermacher\ntags:\n- axolotl\n- generated_from_trainer\n- phi\n- phi2\n- einstein\n- instruct\n- finetune\n- chatml\n- gpt4\n- synthetic data\n- science\n- physics\n- chemistry\n- biology\n- math\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/Weyaxi/Einstein-v4-Qwen-1.5-32B\n\n<!-- provided-files -->\nstatic quants are available at https://huggingface.co/mradermacher/Einstein-v4-Qwen-1.5-32B-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/Einstein-v4-Qwen-1.5-32B-i1-GGUF/resolve/main/Einstein-v4-Qwen-1.5-32B.i1-IQ1_S.gguf) | i1-IQ1_S | 7.3 | for the desperate |\n| [GGUF](https://huggingface.co/mradermacher/Einstein-v4-Qwen-1.5-32B-i1-GGUF/resolve/main/Einstein-v4-Qwen-1.5-32B.i1-IQ1_M.gguf) | i1-IQ1_M | 8.0 | mostly desperate |\n| [GGUF](https://huggingface.co/mradermacher/Einstein-v4-Qwen-1.5-32B-i1-GGUF/resolve/main/Einstein-v4-Qwen-1.5-32B.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 9.1 |  |\n| [GGUF](https://huggingface.co/mradermacher/Einstein-v4-Qwen-1.5-32B-i1-GGUF/resolve/main/Einstein-v4-Qwen-1.5-32B.i1-IQ2_XS.gguf) | i1-IQ2_XS | 10.0 |  |\n| [GGUF](https://huggingface.co/mradermacher/Einstein-v4-Qwen-1.5-32B-i1-GGUF/resolve/main/Einstein-v4-Qwen-1.5-32B.i1-IQ2_S.gguf) | i1-IQ2_S | 10.4 |  |\n| [GGUF](https://huggingface.co/mradermacher/Einstein-v4-Qwen-1.5-32B-i1-GGUF/resolve/main/Einstein-v4-Qwen-1.5-32B.i1-IQ2_M.gguf) | i1-IQ2_M | 11.3 |  |\n| [GGUF](https://huggingface.co/mradermacher/Einstein-v4-Qwen-1.5-32B-i1-GGUF/resolve/main/Einstein-v4-Qwen-1.5-32B.i1-Q2_K.gguf) | i1-Q2_K | 12.3 | IQ3_XXS probably better |\n| [GGUF](https://huggingface.co/mradermacher/Einstein-v4-Qwen-1.5-32B-i1-GGUF/resolve/main/Einstein-v4-Qwen-1.5-32B.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 12.8 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/Einstein-v4-Qwen-1.5-32B-i1-GGUF/resolve/main/Einstein-v4-Qwen-1.5-32B.i1-IQ3_XS.gguf) | i1-IQ3_XS | 13.7 |  |\n| [GGUF](https://huggingface.co/mradermacher/Einstein-v4-Qwen-1.5-32B-i1-GGUF/resolve/main/Einstein-v4-Qwen-1.5-32B.i1-Q3_K_S.gguf) | i1-Q3_K_S | 14.4 | IQ3_XS probably better |\n| [GGUF](https://huggingface.co/mradermacher/Einstein-v4-Qwen-1.5-32B-i1-GGUF/resolve/main/Einstein-v4-Qwen-1.5-32B.i1-IQ3_S.gguf) | i1-IQ3_S | 14.4 | beats Q3_K* |\n| [GGUF](https://huggingface.co/mradermacher/Einstein-v4-Qwen-1.5-32B-i1-GGUF/resolve/main/Einstein-v4-Qwen-1.5-32B.i1-IQ3_M.gguf) | i1-IQ3_M | 14.8 |  |\n| [GGUF](https://huggingface.co/mradermacher/Einstein-v4-Qwen-1.5-32B-i1-GGUF/resolve/main/Einstein-v4-Qwen-1.5-32B.i1-Q3_K_M.gguf) | i1-Q3_K_M | 15.9 | IQ3_S probably better |\n| [GGUF](https://huggingface.co/mradermacher/Einstein-v4-Qwen-1.5-32B-i1-GGUF/resolve/main/Einstein-v4-Qwen-1.5-32B.i1-Q3_K_L.gguf) | i1-Q3_K_L | 17.2 | IQ3_M probably better |\n| [GGUF](https://huggingface.co/mradermacher/Einstein-v4-Qwen-1.5-32B-i1-GGUF/resolve/main/Einstein-v4-Qwen-1.5-32B.i1-IQ4_XS.gguf) | i1-IQ4_XS | 17.7 |  |\n| [GGUF](https://huggingface.co/mradermacher/Einstein-v4-Qwen-1.5-32B-i1-GGUF/resolve/main/Einstein-v4-Qwen-1.5-32B.i1-Q4_0.gguf) | i1-Q4_0 | 18.7 | fast, low quality |\n| [GGUF](https://huggingface.co/mradermacher/Einstein-v4-Qwen-1.5-32B-i1-GGUF/resolve/main/Einstein-v4-Qwen-1.5-32B.i1-Q4_K_S.gguf) | i1-Q4_K_S | 18.7 | optimal size/speed/quality |\n| [GGUF](https://huggingface.co/mradermacher/Einstein-v4-Qwen-1.5-32B-i1-GGUF/resolve/main/Einstein-v4-Qwen-1.5-32B.i1-Q4_K_M.gguf) | i1-Q4_K_M | 19.8 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/Einstein-v4-Qwen-1.5-32B-i1-GGUF/resolve/main/Einstein-v4-Qwen-1.5-32B.i1-Q5_K_S.gguf) | i1-Q5_K_S | 22.6 |  |\n| [GGUF](https://huggingface.co/mradermacher/Einstein-v4-Qwen-1.5-32B-i1-GGUF/resolve/main/Einstein-v4-Qwen-1.5-32B.i1-Q5_K_M.gguf) | i1-Q5_K_M | 23.2 |  |\n| [GGUF](https://huggingface.co/mradermacher/Einstein-v4-Qwen-1.5-32B-i1-GGUF/resolve/main/Einstein-v4-Qwen-1.5-32B.i1-Q6_K.gguf) | i1-Q6_K | 26.8 | 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": [
    "transformers",
    "gguf",
    "axolotl",
    "generated_from_trainer",
    "phi",
    "phi2",
    "einstein",
    "instruct",
    "finetune",
    "chatml",
    "gpt4",
    "synthetic data",
    "science",
    "physics",
    "chemistry",
    "biology",
    "math",
    "en",
    "dataset:allenai/ai2_arc",
    "dataset:camel-ai/physics",
    "dataset:camel-ai/chemistry",
    "dataset:camel-ai/biology",
    "dataset:camel-ai/math",
    "dataset:metaeval/reclor",
    "dataset:openbookqa",
    "dataset:mandyyyyii/scibench",
    "dataset:derek-thomas/ScienceQA",
    "dataset:TIGER-Lab/ScienceEval",
    "dataset:jondurbin/airoboros-3.2",
    "dataset:LDJnr/Capybara",
    "dataset:Cot-Alpaca-GPT4-From-OpenHermes-2.5",
    "dataset:STEM-AI-mtl/Electrical-engineering",
    "dataset:knowrohit07/saraswati-stem",
    "dataset:sablo/oasst2_curated",
    "dataset:glaiveai/glaive-code-assistant",
    "dataset:lmsys/lmsys-chat-1m",
    "dataset:TIGER-Lab/MathInstruct",
    "dataset:bigbio/med_qa",
    "dataset:meta-math/MetaMathQA-40K",
    "dataset:piqa",
    "dataset:scibench",
    "dataset:sciq",
    "dataset:Open-Orca/SlimOrca",
    "dataset:migtissera/Synthia-v1.3",
    "base_model:Weyaxi/Einstein-v4-Qwen-1.5-32B",
    "base_model:quantized:Weyaxi/Einstein-v4-Qwen-1.5-32B",
    "license:other",
    "endpoints_compatible",
    "region:us",
    "imatrix",
    "conversational"
  ],
  "likes": 3,
  "downloads": 223,
  "gated": false,
  "private": false,
  "last_modified": "2024-08-02T10:31:57.000Z",
  "created_at": "2024-06-16T21:51:10.000Z",
  "pipeline_tag": "",
  "library_name": "transformers"
}

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