mradermacher/llama-3-instruct-neurona-8b-v2-gguf overview

{
  "metadata": {},
  "card_data": {
    "base_model": "Iker/Llama-3-Instruct-Neurona-8b-v2",
    "datasets": [
      "Danielbrdz/Barcenas-Economia",
      "HiTZ/casimedicos-exp",
      "somosnlp/coser_resumenes",
      "csebuetnlp/CrossSum",
      "Iker/Document-Translation-en-es",
      "somosnlp/es-inclusive-language-it",
      "glaiveai/glaive-code-assistant-v3",
      "glaiveai/glaive-function-calling-v2",
      "Iker/InstructTranslation-EN-ES",
      "somosnlp/lenguaje-claro-dataset",
      "somosnlp/LingComp_QA",
      "Iker/NoticIA",
      "teknium/OpenHermes-2.5",
      "Iker/OpenHermes-2.5-Spanish",
      "Helsinki-NLP/opus-100",
      "projecte-aina/RAG_Multilingual",
      "HiTZ/This-is-not-a-dataset",
      "Iker/Reddit-Post-Translation",
      "wikipedia"
    ],
    "language": [
      "es",
      "en"
    ],
    "library_name": "transformers",
    "license": "llama3",
    "quantized_by": "mradermacher",
    "tags": [
      "synthetic"
    ],
    "frontmatter": {
      "base_model": "Iker/Llama-3-Instruct-Neurona-8b-v2",
      "datasets": [
        "Danielbrdz/Barcenas-Economia",
        "HiTZ/casimedicos-exp",
        "somosnlp/coser_resumenes",
        "csebuetnlp/CrossSum",
        "Iker/Document-Translation-en-es",
        "somosnlp/es-inclusive-language-it",
        "glaiveai/glaive-code-assistant-v3",
        "glaiveai/glaive-function-calling-v2",
        "Iker/InstructTranslation-EN-ES",
        "somosnlp/lenguaje-claro-dataset",
        "somosnlp/LingComp_QA",
        "Iker/NoticIA",
        "teknium/OpenHermes-2.5",
        "Iker/OpenHermes-2.5-Spanish",
        "Helsinki-NLP/opus-100",
        "projecte-aina/RAG_Multilingual",
        "HiTZ/This-is-not-a-dataset",
        "Iker/Reddit-Post-Translation",
        "wikipedia"
      ],
      "language": [
        "es",
        "en"
      ],
      "library_name": "transformers",
      "license": "llama3",
      "quantized_by": "mradermacher",
      "tags": [
        "synthetic"
      ]
    },
    "hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
    "summary": "## About      static quants of https://huggingface.co/Iker/Llama-3-Instruct-Neurona-8b-v2  weighted/imatrix quants are available at https://huggingface.co/mradermacher/Llama-3-Instruct-Neurona-8b-v2-i1-GGUF",
    "quick_links": [],
    "benchmark_table_html": "",
    "readme_markdown": "---\nbase_model: Iker/Llama-3-Instruct-Neurona-8b-v2\ndatasets:\n- Danielbrdz/Barcenas-Economia\n- HiTZ/casimedicos-exp\n- somosnlp/coser_resumenes\n- csebuetnlp/CrossSum\n- Iker/Document-Translation-en-es\n- somosnlp/es-inclusive-language-it\n- glaiveai/glaive-code-assistant-v3\n- glaiveai/glaive-function-calling-v2\n- Iker/InstructTranslation-EN-ES\n- somosnlp/lenguaje-claro-dataset\n- somosnlp/LingComp_QA\n- Iker/NoticIA\n- teknium/OpenHermes-2.5\n- Iker/OpenHermes-2.5-Spanish\n- Helsinki-NLP/opus-100\n- projecte-aina/RAG_Multilingual\n- HiTZ/This-is-not-a-dataset\n- Iker/Reddit-Post-Translation\n- wikipedia\nlanguage:\n- es\n- en\nlibrary_name: transformers\nlicense: llama3\nquantized_by: mradermacher\ntags:\n- synthetic\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/Iker/Llama-3-Instruct-Neurona-8b-v2\n\n<!-- provided-files -->\nweighted/imatrix quants are available at https://huggingface.co/mradermacher/Llama-3-Instruct-Neurona-8b-v2-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/Llama-3-Instruct-Neurona-8b-v2-GGUF/resolve/main/Llama-3-Instruct-Neurona-8b-v2.Q2_K.gguf) | Q2_K | 3.3 |  |\n| [GGUF](https://huggingface.co/mradermacher/Llama-3-Instruct-Neurona-8b-v2-GGUF/resolve/main/Llama-3-Instruct-Neurona-8b-v2.IQ3_XS.gguf) | IQ3_XS | 3.6 |  |\n| [GGUF](https://huggingface.co/mradermacher/Llama-3-Instruct-Neurona-8b-v2-GGUF/resolve/main/Llama-3-Instruct-Neurona-8b-v2.Q3_K_S.gguf) | Q3_K_S | 3.8 |  |\n| [GGUF](https://huggingface.co/mradermacher/Llama-3-Instruct-Neurona-8b-v2-GGUF/resolve/main/Llama-3-Instruct-Neurona-8b-v2.IQ3_S.gguf) | IQ3_S | 3.8 | beats Q3_K* |\n| [GGUF](https://huggingface.co/mradermacher/Llama-3-Instruct-Neurona-8b-v2-GGUF/resolve/main/Llama-3-Instruct-Neurona-8b-v2.IQ3_M.gguf) | IQ3_M | 3.9 |  |\n| [GGUF](https://huggingface.co/mradermacher/Llama-3-Instruct-Neurona-8b-v2-GGUF/resolve/main/Llama-3-Instruct-Neurona-8b-v2.Q3_K_M.gguf) | Q3_K_M | 4.1 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/Llama-3-Instruct-Neurona-8b-v2-GGUF/resolve/main/Llama-3-Instruct-Neurona-8b-v2.Q3_K_L.gguf) | Q3_K_L | 4.4 |  |\n| [GGUF](https://huggingface.co/mradermacher/Llama-3-Instruct-Neurona-8b-v2-GGUF/resolve/main/Llama-3-Instruct-Neurona-8b-v2.IQ4_XS.gguf) | IQ4_XS | 4.6 |  |\n| [GGUF](https://huggingface.co/mradermacher/Llama-3-Instruct-Neurona-8b-v2-GGUF/resolve/main/Llama-3-Instruct-Neurona-8b-v2.Q4_K_S.gguf) | Q4_K_S | 4.8 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/Llama-3-Instruct-Neurona-8b-v2-GGUF/resolve/main/Llama-3-Instruct-Neurona-8b-v2.Q4_K_M.gguf) | Q4_K_M | 5.0 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/Llama-3-Instruct-Neurona-8b-v2-GGUF/resolve/main/Llama-3-Instruct-Neurona-8b-v2.Q5_K_S.gguf) | Q5_K_S | 5.7 |  |\n| [GGUF](https://huggingface.co/mradermacher/Llama-3-Instruct-Neurona-8b-v2-GGUF/resolve/main/Llama-3-Instruct-Neurona-8b-v2.Q5_K_M.gguf) | Q5_K_M | 5.8 |  |\n| [GGUF](https://huggingface.co/mradermacher/Llama-3-Instruct-Neurona-8b-v2-GGUF/resolve/main/Llama-3-Instruct-Neurona-8b-v2.Q6_K.gguf) | Q6_K | 6.7 | very good quality |\n| [GGUF](https://huggingface.co/mradermacher/Llama-3-Instruct-Neurona-8b-v2-GGUF/resolve/main/Llama-3-Instruct-Neurona-8b-v2.Q8_0.gguf) | Q8_0 | 8.6 | fast, best quality |\n| [GGUF](https://huggingface.co/mradermacher/Llama-3-Instruct-Neurona-8b-v2-GGUF/resolve/main/Llama-3-Instruct-Neurona-8b-v2.f16.gguf) | f16 | 16.2 | 16 bpw, overkill |\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": [
    "transformers",
    "gguf",
    "synthetic",
    "es",
    "en",
    "dataset:Danielbrdz/Barcenas-Economia",
    "dataset:HiTZ/casimedicos-exp",
    "dataset:somosnlp/coser_resumenes",
    "dataset:csebuetnlp/CrossSum",
    "dataset:Iker/Document-Translation-en-es",
    "dataset:somosnlp/es-inclusive-language-it",
    "dataset:glaiveai/glaive-code-assistant-v3",
    "dataset:glaiveai/glaive-function-calling-v2",
    "dataset:Iker/InstructTranslation-EN-ES",
    "dataset:somosnlp/lenguaje-claro-dataset",
    "dataset:somosnlp/LingComp_QA",
    "dataset:Iker/NoticIA",
    "dataset:teknium/OpenHermes-2.5",
    "dataset:Iker/OpenHermes-2.5-Spanish",
    "dataset:Helsinki-NLP/opus-100",
    "dataset:projecte-aina/RAG_Multilingual",
    "dataset:HiTZ/This-is-not-a-dataset",
    "dataset:Iker/Reddit-Post-Translation",
    "dataset:wikipedia",
    "base_model:Iker/Llama-3-Instruct-Neurona-8b-v2",
    "base_model:quantized:Iker/Llama-3-Instruct-Neurona-8b-v2",
    "license:llama3",
    "endpoints_compatible",
    "region:us",
    "conversational"
  ],
  "likes": 0,
  "downloads": 182,
  "gated": false,
  "private": false,
  "last_modified": "2024-07-02T03:13:42.000Z",
  "created_at": "2024-07-01T17:57:21.000Z",
  "pipeline_tag": "",
  "library_name": "transformers"
}

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