mradermacher/linkbricks-horizon-ai-korean-superb-27b-gguf overview

{
  "metadata": {},
  "card_data": {
    "base_model": "Saxo/Linkbricks-Horizon-AI-Korean-Superb-27B",
    "datasets": [
      "Saxo/ko_cn_translation_tech_social_science_linkbricks_single_dataset",
      "Saxo/ko_jp_translation_tech_social_science_linkbricks_single_dataset",
      "Saxo/en_ko_translation_tech_science_linkbricks_single_dataset_with_prompt_text_huggingface",
      "Saxo/en_ko_translation_social_science_linkbricks_single_dataset_with_prompt_text_huggingface",
      "Saxo/ko_aspect_sentiment_sns_mall_sentiment_linkbricks_single_dataset_with_prompt_text_huggingface",
      "Saxo/ko_summarization_linkbricks_single_dataset_with_prompt_text_huggingface",
      "Saxo/OpenOrca_cleaned_kor_linkbricks_single_dataset_with_prompt_text_huggingface",
      "Saxo/ko_government_qa_total_linkbricks_single_dataset_with_prompt_text_huggingface_sampled",
      "Saxo/ko-news-corpus-1",
      "Saxo/ko-news-corpus-2",
      "Saxo/ko-news-corpus-3",
      "Saxo/ko-news-corpus-4",
      "Saxo/ko-news-corpus-5",
      "Saxo/ko-news-corpus-6",
      "Saxo/ko-news-corpus-7",
      "Saxo/ko-news-corpus-8",
      "Saxo/ko-news-corpus-9",
      "maywell/ko_Ultrafeedback_binarized",
      "youjunhyeok/ko-orca-pair-and-ultrafeedback-dpo",
      "lilacai/glaive-function-calling-v2-sharegpt",
      "kuotient/gsm8k-ko"
    ],
    "language": [
      "ko",
      "en",
      "jp",
      "cn"
    ],
    "library_name": "transformers",
    "license": "apache-2.0",
    "quantized_by": "mradermacher",
    "frontmatter": {
      "base_model": "Saxo/Linkbricks-Horizon-AI-Korean-Superb-27B",
      "datasets": [
        "Saxo/ko_cn_translation_tech_social_science_linkbricks_single_dataset",
        "Saxo/ko_jp_translation_tech_social_science_linkbricks_single_dataset",
        "Saxo/en_ko_translation_tech_science_linkbricks_single_dataset_with_prompt_text_huggingface",
        "Saxo/en_ko_translation_social_science_linkbricks_single_dataset_with_prompt_text_huggingface",
        "Saxo/ko_aspect_sentiment_sns_mall_sentiment_linkbricks_single_dataset_with_prompt_text_huggingface",
        "Saxo/ko_summarization_linkbricks_single_dataset_with_prompt_text_huggingface",
        "Saxo/OpenOrca_cleaned_kor_linkbricks_single_dataset_with_prompt_text_huggingface",
        "Saxo/ko_government_qa_total_linkbricks_single_dataset_with_prompt_text_huggingface_sampled",
        "Saxo/ko-news-corpus-1",
        "Saxo/ko-news-corpus-2",
        "Saxo/ko-news-corpus-3",
        "Saxo/ko-news-corpus-4",
        "Saxo/ko-news-corpus-5",
        "Saxo/ko-news-corpus-6",
        "Saxo/ko-news-corpus-7",
        "Saxo/ko-news-corpus-8",
        "Saxo/ko-news-corpus-9",
        "maywell/ko_Ultrafeedback_binarized",
        "youjunhyeok/ko-orca-pair-and-ultrafeedback-dpo",
        "lilacai/glaive-function-calling-v2-sharegpt",
        "kuotient/gsm8k-ko"
      ],
      "language": [
        "ko",
        "en",
        "jp",
        "cn"
      ],
      "library_name": "transformers",
      "license": "apache-2.0",
      "quantized_by": "mradermacher"
    },
    "hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
    "summary": "## About      static quants of https://huggingface.co/Saxo/Linkbricks-Horizon-AI-Korean-Superb-27B  weighted/imatrix quants are available at https://huggingface.co/mradermacher/Linkbricks-Horizon-AI-Korean-Superb-27B-i1-GGUF",
    "quick_links": [],
    "benchmark_table_html": "",
    "readme_markdown": "---\nbase_model: Saxo/Linkbricks-Horizon-AI-Korean-Superb-27B\ndatasets:\n- Saxo/ko_cn_translation_tech_social_science_linkbricks_single_dataset\n- Saxo/ko_jp_translation_tech_social_science_linkbricks_single_dataset\n- Saxo/en_ko_translation_tech_science_linkbricks_single_dataset_with_prompt_text_huggingface\n- Saxo/en_ko_translation_social_science_linkbricks_single_dataset_with_prompt_text_huggingface\n- Saxo/ko_aspect_sentiment_sns_mall_sentiment_linkbricks_single_dataset_with_prompt_text_huggingface\n- Saxo/ko_summarization_linkbricks_single_dataset_with_prompt_text_huggingface\n- Saxo/OpenOrca_cleaned_kor_linkbricks_single_dataset_with_prompt_text_huggingface\n- Saxo/ko_government_qa_total_linkbricks_single_dataset_with_prompt_text_huggingface_sampled\n- Saxo/ko-news-corpus-1\n- Saxo/ko-news-corpus-2\n- Saxo/ko-news-corpus-3\n- Saxo/ko-news-corpus-4\n- Saxo/ko-news-corpus-5\n- Saxo/ko-news-corpus-6\n- Saxo/ko-news-corpus-7\n- Saxo/ko-news-corpus-8\n- Saxo/ko-news-corpus-9\n- maywell/ko_Ultrafeedback_binarized\n- youjunhyeok/ko-orca-pair-and-ultrafeedback-dpo\n- lilacai/glaive-function-calling-v2-sharegpt\n- kuotient/gsm8k-ko\nlanguage:\n- ko\n- en\n- jp\n- cn\nlibrary_name: transformers\nlicense: apache-2.0\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: nicoboss -->\nstatic quants of https://huggingface.co/Saxo/Linkbricks-Horizon-AI-Korean-Superb-27B\n\n<!-- provided-files -->\nweighted/imatrix quants are available at https://huggingface.co/mradermacher/Linkbricks-Horizon-AI-Korean-Superb-27B-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/Linkbricks-Horizon-AI-Korean-Superb-27B-GGUF/resolve/main/Linkbricks-Horizon-AI-Korean-Superb-27B.Q2_K.gguf) | Q2_K | 10.5 |  |\n| [GGUF](https://huggingface.co/mradermacher/Linkbricks-Horizon-AI-Korean-Superb-27B-GGUF/resolve/main/Linkbricks-Horizon-AI-Korean-Superb-27B.Q3_K_S.gguf) | Q3_K_S | 12.3 |  |\n| [GGUF](https://huggingface.co/mradermacher/Linkbricks-Horizon-AI-Korean-Superb-27B-GGUF/resolve/main/Linkbricks-Horizon-AI-Korean-Superb-27B.Q3_K_M.gguf) | Q3_K_M | 13.5 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/Linkbricks-Horizon-AI-Korean-Superb-27B-GGUF/resolve/main/Linkbricks-Horizon-AI-Korean-Superb-27B.Q3_K_L.gguf) | Q3_K_L | 14.6 |  |\n| [GGUF](https://huggingface.co/mradermacher/Linkbricks-Horizon-AI-Korean-Superb-27B-GGUF/resolve/main/Linkbricks-Horizon-AI-Korean-Superb-27B.IQ4_XS.gguf) | IQ4_XS | 15.0 |  |\n| [GGUF](https://huggingface.co/mradermacher/Linkbricks-Horizon-AI-Korean-Superb-27B-GGUF/resolve/main/Linkbricks-Horizon-AI-Korean-Superb-27B.Q4_K_S.gguf) | Q4_K_S | 15.8 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/Linkbricks-Horizon-AI-Korean-Superb-27B-GGUF/resolve/main/Linkbricks-Horizon-AI-Korean-Superb-27B.Q4_K_M.gguf) | Q4_K_M | 16.7 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/Linkbricks-Horizon-AI-Korean-Superb-27B-GGUF/resolve/main/Linkbricks-Horizon-AI-Korean-Superb-27B.Q5_K_S.gguf) | Q5_K_S | 19.0 |  |\n| [GGUF](https://huggingface.co/mradermacher/Linkbricks-Horizon-AI-Korean-Superb-27B-GGUF/resolve/main/Linkbricks-Horizon-AI-Korean-Superb-27B.Q5_K_M.gguf) | Q5_K_M | 19.5 |  |\n| [GGUF](https://huggingface.co/mradermacher/Linkbricks-Horizon-AI-Korean-Superb-27B-GGUF/resolve/main/Linkbricks-Horizon-AI-Korean-Superb-27B.Q6_K.gguf) | Q6_K | 22.4 | very good quality |\n| [GGUF](https://huggingface.co/mradermacher/Linkbricks-Horizon-AI-Korean-Superb-27B-GGUF/resolve/main/Linkbricks-Horizon-AI-Korean-Superb-27B.Q8_0.gguf) | Q8_0 | 29.0 | 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. 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",
    "ko",
    "en",
    "jp",
    "cn",
    "dataset:Saxo/ko_cn_translation_tech_social_science_linkbricks_single_dataset",
    "dataset:Saxo/ko_jp_translation_tech_social_science_linkbricks_single_dataset",
    "dataset:Saxo/en_ko_translation_tech_science_linkbricks_single_dataset_with_prompt_text_huggingface",
    "dataset:Saxo/en_ko_translation_social_science_linkbricks_single_dataset_with_prompt_text_huggingface",
    "dataset:Saxo/ko_aspect_sentiment_sns_mall_sentiment_linkbricks_single_dataset_with_prompt_text_huggingface",
    "dataset:Saxo/ko_summarization_linkbricks_single_dataset_with_prompt_text_huggingface",
    "dataset:Saxo/OpenOrca_cleaned_kor_linkbricks_single_dataset_with_prompt_text_huggingface",
    "dataset:Saxo/ko_government_qa_total_linkbricks_single_dataset_with_prompt_text_huggingface_sampled",
    "dataset:Saxo/ko-news-corpus-1",
    "dataset:Saxo/ko-news-corpus-2",
    "dataset:Saxo/ko-news-corpus-3",
    "dataset:Saxo/ko-news-corpus-4",
    "dataset:Saxo/ko-news-corpus-5",
    "dataset:Saxo/ko-news-corpus-6",
    "dataset:Saxo/ko-news-corpus-7",
    "dataset:Saxo/ko-news-corpus-8",
    "dataset:Saxo/ko-news-corpus-9",
    "dataset:maywell/ko_Ultrafeedback_binarized",
    "dataset:youjunhyeok/ko-orca-pair-and-ultrafeedback-dpo",
    "dataset:lilacai/glaive-function-calling-v2-sharegpt",
    "dataset:kuotient/gsm8k-ko",
    "base_model:Saxo/Linkbricks-Horizon-AI-Korean-Superb-27B",
    "base_model:quantized:Saxo/Linkbricks-Horizon-AI-Korean-Superb-27B",
    "license:apache-2.0",
    "endpoints_compatible",
    "region:us",
    "conversational"
  ],
  "likes": 1,
  "downloads": 226,
  "gated": false,
  "private": false,
  "last_modified": "2024-12-04T11:40:22.000Z",
  "created_at": "2024-12-03T19:51:54.000Z",
  "pipeline_tag": "",
  "library_name": "transformers"
}

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