mradermacher/qwen1.5-0.5b-xia-ai-gguf overview

{
  "metadata": {},
  "card_data": {
    "base_model": "win10/Qwen1.5-0.5b-Xia-Ai",
    "datasets": [
      "c-s-ale/alpaca-gpt4-data-zh",
      "sahil2801/CodeAlpaca-20k",
      "TIGER-Lab/MathInstruct"
    ],
    "language": [
      "en",
      "zh"
    ],
    "library_name": "transformers",
    "license": "other",
    "license_link": "https://huggingface.co/Qwen/Qwen1.5-72B-Chat/blob/main/LICENSE",
    "license_name": "tongyi-qianwen",
    "quantized_by": "mradermacher",
    "frontmatter": {
      "base_model": "win10/Qwen1.5-0.5b-Xia-Ai",
      "datasets": [
        "c-s-ale/alpaca-gpt4-data-zh",
        "sahil2801/CodeAlpaca-20k",
        "TIGER-Lab/MathInstruct"
      ],
      "language": [
        "en",
        "zh"
      ],
      "library_name": "transformers",
      "license": "other",
      "license_link": "https://huggingface.co/Qwen/Qwen1.5-72B-Chat/blob/main/LICENSE",
      "license_name": "tongyi-qianwen",
      "quantized_by": "mradermacher"
    },
    "hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
    "summary": "## About      static quants of https://huggingface.co/win10/Qwen1.5-0.5b-Xia-Ai  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: win10/Qwen1.5-0.5b-Xia-Ai\ndatasets:\n- c-s-ale/alpaca-gpt4-data-zh\n- sahil2801/CodeAlpaca-20k\n- TIGER-Lab/MathInstruct\nlanguage:\n- en\n- zh\nlibrary_name: transformers\nlicense: other\nlicense_link: https://huggingface.co/Qwen/Qwen1.5-72B-Chat/blob/main/LICENSE\nlicense_name: tongyi-qianwen\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:  -->\nstatic quants of https://huggingface.co/win10/Qwen1.5-0.5b-Xia-Ai\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/Qwen1.5-0.5b-Xia-Ai-GGUF/resolve/main/Qwen1.5-0.5b-Xia-Ai.Q2_K.gguf) | Q2_K | 0.3 |  |\n| [GGUF](https://huggingface.co/mradermacher/Qwen1.5-0.5b-Xia-Ai-GGUF/resolve/main/Qwen1.5-0.5b-Xia-Ai.Q3_K_S.gguf) | Q3_K_S | 0.4 |  |\n| [GGUF](https://huggingface.co/mradermacher/Qwen1.5-0.5b-Xia-Ai-GGUF/resolve/main/Qwen1.5-0.5b-Xia-Ai.Q3_K_M.gguf) | Q3_K_M | 0.4 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/Qwen1.5-0.5b-Xia-Ai-GGUF/resolve/main/Qwen1.5-0.5b-Xia-Ai.Q3_K_L.gguf) | Q3_K_L | 0.4 |  |\n| [GGUF](https://huggingface.co/mradermacher/Qwen1.5-0.5b-Xia-Ai-GGUF/resolve/main/Qwen1.5-0.5b-Xia-Ai.IQ4_XS.gguf) | IQ4_XS | 0.4 |  |\n| [GGUF](https://huggingface.co/mradermacher/Qwen1.5-0.5b-Xia-Ai-GGUF/resolve/main/Qwen1.5-0.5b-Xia-Ai.Q4_K_S.gguf) | Q4_K_S | 0.4 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/Qwen1.5-0.5b-Xia-Ai-GGUF/resolve/main/Qwen1.5-0.5b-Xia-Ai.Q4_K_M.gguf) | Q4_K_M | 0.4 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/Qwen1.5-0.5b-Xia-Ai-GGUF/resolve/main/Qwen1.5-0.5b-Xia-Ai.Q5_K_S.gguf) | Q5_K_S | 0.4 |  |\n| [GGUF](https://huggingface.co/mradermacher/Qwen1.5-0.5b-Xia-Ai-GGUF/resolve/main/Qwen1.5-0.5b-Xia-Ai.Q5_K_M.gguf) | Q5_K_M | 0.5 |  |\n| [GGUF](https://huggingface.co/mradermacher/Qwen1.5-0.5b-Xia-Ai-GGUF/resolve/main/Qwen1.5-0.5b-Xia-Ai.Q6_K.gguf) | Q6_K | 0.5 | very good quality |\n| [GGUF](https://huggingface.co/mradermacher/Qwen1.5-0.5b-Xia-Ai-GGUF/resolve/main/Qwen1.5-0.5b-Xia-Ai.Q8_0.gguf) | Q8_0 | 0.6 | fast, best quality |\n| [GGUF](https://huggingface.co/mradermacher/Qwen1.5-0.5b-Xia-Ai-GGUF/resolve/main/Qwen1.5-0.5b-Xia-Ai.f16.gguf) | f16 | 1.0 | 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",
    "en",
    "zh",
    "dataset:c-s-ale/alpaca-gpt4-data-zh",
    "dataset:sahil2801/CodeAlpaca-20k",
    "dataset:TIGER-Lab/MathInstruct",
    "base_model:win10/Qwen1.5-0.5b-Xia-Ai",
    "base_model:quantized:win10/Qwen1.5-0.5b-Xia-Ai",
    "license:other",
    "endpoints_compatible",
    "region:us",
    "conversational"
  ],
  "likes": 0,
  "downloads": 141,
  "gated": false,
  "private": false,
  "last_modified": "2024-11-01T04:12:33.000Z",
  "created_at": "2024-11-01T04:10:06.000Z",
  "pipeline_tag": "",
  "library_name": "transformers"
}

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  "createdAt": "2024-11-01T04:10:06.000Z",
  "lastModified": "2024-11-01T04:12:33.000Z",
  "author": "mradermacher",
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