brittlewis12/gemma-3-1b-it-gguf overview

{
  "metadata": {},
  "card_data": {
    "base_model": "google/gemma-3-1b-it",
    "pipeline_tag": "text-generation",
    "inference": true,
    "language": [
      "en"
    ],
    "license": "gemma",
    "model_creator": "google",
    "model_name": "gemma-3-1b-it",
    "model_type": "gemma3_text",
    "quantized_by": "brittlewis12",
    "tags": [
      "reasoning",
      "gemma"
    ],
    "frontmatter": {
      "base_model": "google/gemma-3-1b-it",
      "pipeline_tag": "text-generation",
      "inference": "true",
      "language": [
        "en"
      ],
      "license": "gemma",
      "model_creator": "google",
      "model_name": "gemma-3-1b-it",
      "model_type": "gemma3_text",
      "quantized_by": "brittlewis12",
      "tags": [
        "reasoning",
        "gemma"
      ]
    },
    "hero_image_url": "https://pbs.twimg.com/profile_images/1744049151241797632/0mIP-P9e_400x400.jpg",
    "summary": "**Original model**: Gemma 3 1B IT **Model creator**: Google DeepMind > Gemma is a family of lightweight, state-of-the-art open models from Google, built from the same research and technology used to create the Gemini models. > Gemma 3 has a large, 128K context window, multilingual support in over 140 languages, and is available in more sizes than previous versions. Gemma 3 models are well-suited for a variety of text generation and image understanding tasks, including question answering, summarization, and reasoning. Their relatively small size makes it possible to deploy them in environments with limited resources such as laptops, desktops or your own cloud infrastructure, democratizing access to state of the art AI models and helping foster innovation for everyone. This repo contains GGUF format model files for Google DeepMind’s Gemma 3 1B IT (instruction-tuned). ### What is GGUF? GGUF is a file format for representing AI models. It is the third version of the format, introduced by the llama.cpp team on August 21st 2023. Converted with llama.cpp build b4875 (revision 7841fc7), using autogguf-rs. ### Prompt template: Gemma Instruct `` {{system_prompt}} user {{prompt}} model `` ---",
    "quick_links": [],
    "benchmark_table_html": "",
    "readme_markdown": "---\nbase_model: google/gemma-3-1b-it\npipeline_tag: text-generation\ninference: true\nlanguage:\n- en\nlicense: gemma\nmodel_creator: google\nmodel_name: gemma-3-1b-it\nmodel_type: gemma3_text\nquantized_by: brittlewis12\ntags:\n- reasoning\n- gemma\n---\n\n# Gemma 3 1B IT GGUF\n\n**Original model**: [Gemma 3 1B IT](https://huggingface.co/google/gemma-3-1b-it)\n\n**Model creator**: [Google DeepMind](https://huggingface.co/google)\n\n> Gemma is a family of lightweight, state-of-the-art open models from Google, built from the same research and technology used to create the Gemini models. \n\n> Gemma 3 has a large, 128K context window, multilingual support in over 140 languages, and is available in more sizes than previous versions. Gemma 3 models are well-suited for a variety of text generation and image understanding tasks, including question answering, summarization, and reasoning. Their relatively small size makes it possible to deploy them in environments with limited resources such as laptops, desktops or your own cloud infrastructure, democratizing access to state of the art AI models and helping foster innovation for everyone.\n\nThis repo contains GGUF format model files for Google DeepMind’s Gemma 3 1B IT (instruction-tuned).\n\n### What is GGUF?\n\nGGUF is a file format for representing AI models. It is the third version of the format, \nintroduced by the llama.cpp team on August 21st 2023.\n\nConverted with llama.cpp build b4875 (revision [7841fc7](https://github.com/ggml-org/llama.cpp/commits/7841fc723e059d1fd9640e5c0ef19050fcc7c698)),\nusing [autogguf-rs](https://github.com/brittlewis12/autogguf-rs).\n\n### Prompt template: [Gemma Instruct](https://huggingface.co/google/gemma-3-1b-it/raw/main/tokenizer_config.json)\n\n```\n{{system_prompt}}\n<start_of_turn>user\n{{prompt}}<end_of_turn>\n<start_of_turn>model\n\n\n```\n\n---\n\n## Download & run with [cnvrs](https://twitter.com/cnvrsai) on iPhone, iPad, and Mac!\n\n![cnvrs.ai](https://pbs.twimg.com/profile_images/1744049151241797632/0mIP-P9e_400x400.jpg)\n\n[cnvrs](https://testflight.apple.com/join/sFWReS7K) is the best app for private, local AI on your device:\n- create & save **Characters** with custom system prompts & temperature settings\n- download and experiment with any **GGUF model** you can [find on HuggingFace](https://huggingface.co/models?library=gguf)!\n    * or, use an API key with the chat completions-compatible model provider of your choice -- ChatGPT, Claude, Gemini, DeepSeek, & more!\n- make it your own with custom **Theme colors**\n- powered by Metal ⚡️ & [Llama.cpp](https://github.com/ggml-org/llama.cpp), with **haptics** during response streaming!\n- **try it out** yourself today, on [Testflight](https://testflight.apple.com/join/sFWReS7K)!\n    * if you **already have the app**, download Gemma 3 1B IT now! \n    * <cnvrsai:///models/search/hf?id=brittlewis12/gemma-3-1b-it-GGUF>\n- follow [cnvrs on twitter](https://twitter.com/cnvrsai) to stay up to date\n\n### Gemma 3 1B IT in cnvrs on macOS\n\n![gemma-3 in cnvrs](https://cdn-uploads.huggingface.co/production/uploads/63b64d7a889aa6707f155cdb/dt0eLAU9pKyKnuu8oCw0D.png)\n\n---\n\n## Original Model Evaluation\n\n> These models were evaluated against a large collection of different datasets and\nmetrics to cover different aspects of text generation:\n\n#### Reasoning and factuality\n\n| Benchmark                      | Metric         | Gemma 3 PT 1B  | Gemma 3 PT 4B | Gemma 3 PT 12B | Gemma 3 PT 27B |\n| ------------------------------ |----------------|:--------------:|:-------------:|:--------------:|:--------------:|\n| [HellaSwag][hellaswag]         | 10-shot        |      62.3      |      77.2     |      84.2      |      85.6      |\n| [BoolQ][boolq]                 | 0-shot         |      63.2      |      72.3     |      78.8      |      82.4      |\n| [PIQA][piqa]                   | 0-shot         |      73.8      |      79.6     |      81.8      |      83.3      |\n| [SocialIQA][socialiqa]         | 0-shot         |      48.9      |      51.9     |      53.4      |      54.9      |\n| [TriviaQA][triviaqa]           | 5-shot         |      39.8      |      65.8     |      78.2      |      85.5      |\n| [Natural Questions][naturalq]  | 5-shot         |      9.48      |      20.0     |      31.4      |      36.1      |\n| [ARC-c][arc]                   | 25-shot        |      38.4      |      56.2     |      68.9      |      70.6      |\n| [ARC-e][arc]                   | 0-shot         |      73.0      |      82.4     |      88.3      |      89.0      |\n| [WinoGrande][winogrande]       | 5-shot         |      58.2      |      64.7     |      74.3      |      78.8      |\n| [BIG-Bench Hard][bbh]          | few-shot       |      28.4      |      50.9     |      72.6      |      77.7      |\n| [DROP][drop]                   | 1-shot         |      42.4      |      60.1     |      72.2      |      77.2      |\n\n[hellaswag]: https://arxiv.org/abs/1905.07830\n[boolq]: https://arxiv.org/abs/1905.10044\n[piqa]: https://arxiv.org/abs/1911.11641\n[socialiqa]: https://arxiv.org/abs/1904.09728\n[triviaqa]: https://arxiv.org/abs/1705.03551\n[naturalq]: https://github.com/google-research-datasets/natural-questions\n[arc]: https://arxiv.org/abs/1911.01547\n[winogrande]: https://arxiv.org/abs/1907.10641\n[bbh]: https://paperswithcode.com/dataset/bbh\n[drop]: https://arxiv.org/abs/1903.00161\n\n#### Multilingual\n\n| Benchmark                            | Gemma 3 PT 1B | Gemma 3 PT 4B | Gemma 3 PT 12B | Gemma 3 PT 27B |\n| ------------------------------------ |:-------------:|:-------------:|:--------------:|:--------------:|\n| [MGSM][mgsm]                         |      2.04     |      34.7     |      64.3     |      74.3     |\n| [Global-MMLU-Lite][global-mmlu-lite] |      24.9     |      57.0     |      69.4     |      75.7     |\n| [WMT24++][wmt24pp] (ChrF)            |      36.7     |      48.4     |      53.9     |      55.7     |\n| [FloRes][flores]                     |      29.5     |      39.2     |      46.0     |      48.8     |\n| [XQuAD][xquad] (all)                 |      43.9     |      68.0     |      74.5     |      76.8     |\n| [ECLeKTic][eclektic]                 |      4.69     |      11.0     |      17.2     |      24.4     |\n| [IndicGenBench][indicgenbench]       |      41.4     |      57.2     |      61.7     |      63.4     |\n\n[mgsm]: https://arxiv.org/abs/2210.03057\n[flores]: https://arxiv.org/abs/2106.03193\n[xquad]: https://arxiv.org/abs/1910.11856v3\n[global-mmlu-lite]: https://huggingface.co/datasets/CohereForAI/Global-MMLU-Lite\n[wmt24pp]: https://arxiv.org/abs/2502.12404v1\n[eclektic]: https://arxiv.org/abs/2502.21228\n[indicgenbench]: https://arxiv.org/abs/2404.16816\n",
    "related_quantizations": []
  },
  "tags": [
    "gguf",
    "reasoning",
    "gemma",
    "text-generation",
    "en",
    "arxiv:1905.07830",
    "arxiv:1905.10044",
    "arxiv:1911.11641",
    "arxiv:1904.09728",
    "arxiv:1705.03551",
    "arxiv:1911.01547",
    "arxiv:1907.10641",
    "arxiv:1903.00161",
    "arxiv:2210.03057",
    "arxiv:2106.03193",
    "arxiv:1910.11856",
    "arxiv:2502.12404",
    "arxiv:2502.21228",
    "arxiv:2404.16816",
    "base_model:google/gemma-3-1b-it",
    "base_model:quantized:google/gemma-3-1b-it",
    "license:gemma",
    "endpoints_compatible",
    "region:us",
    "conversational"
  ],
  "likes": 2,
  "downloads": 267,
  "gated": false,
  "private": false,
  "last_modified": "2025-03-12T11:56:38.000Z",
  "created_at": "2025-03-12T07:34:13.000Z",
  "pipeline_tag": "text-generation",
  "library_name": ""
}

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  "author": "brittlewis12",
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