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Model Intelligence Sheet

legraphista/datagemma-rig-27b-it-imat-gguf overview

Llama.cpp imatrix quantization of google/datagemma-rig-27b-it Original Model: google/datagemma-rig-27b-it Original dtype: BF16 (bfloat16) Quantized by: llama.cpp b3750 IMatrix dataset: here ---

ggufconversationalquantizedGGUFquantizationimatimatrixstatic16bit8bit6bit5bit4bit3bit2bit1bittext-generationbase_model:google/datagemma-rig-27b-itbase_model:quantized:google/datagemma-rig-27b-itlicense:gemmaregion:us
legraphista/datagemma-rig-27b-it-imat-gguf visual
Downloads
256
Likes
0
Pipeline
text-generation
Library
gguf
Visibility
Public
Access
Open

Repository Files & Downloads

29 files detected
Direct downloads for all repository files
FileTypeQuantizationSizeLink
datagemma-rig-27b-it.BF16-00001-of-00003.gguf GGUF BF16 22.24 GB Download
datagemma-rig-27b-it.BF16-00002-of-00003.gguf GGUF BF16 22.15 GB Download
datagemma-rig-27b-it.BF16-00003-of-00003.gguf GGUF BF16 6.33 GB Download
datagemma-rig-27b-it.FP16-00001-of-00003.gguf GGUF 22.24 GB Download
datagemma-rig-27b-it.FP16-00002-of-00003.gguf GGUF 22.15 GB Download
datagemma-rig-27b-it.FP16-00003-of-00003.gguf GGUF 6.33 GB Download
datagemma-rig-27b-it.IQ1_M.gguf GGUF IQ1_M 6.23 GB Download
datagemma-rig-27b-it.IQ1_S.gguf GGUF IQ1_S 5.71 GB Download
datagemma-rig-27b-it.IQ2_M.gguf GGUF IQ2_M 8.75 GB Download
datagemma-rig-27b-it.IQ2_S.gguf GGUF IQ2_S 8.06 GB Download
datagemma-rig-27b-it.IQ2_XS.gguf GGUF IQ2_XS 7.82 GB Download
datagemma-rig-27b-it.IQ2_XXS.gguf GGUF IQ2_XXS 7.10 GB Download
datagemma-rig-27b-it.IQ3_M.gguf GGUF IQ3_M 11.60 GB Download
datagemma-rig-27b-it.IQ3_S.gguf GGUF IQ3_S 11.33 GB Download
datagemma-rig-27b-it.IQ3_XS.gguf GGUF IQ3_XS 10.76 GB Download
datagemma-rig-27b-it.IQ3_XXS.gguf GGUF IQ3_XXS 10.01 GB Download
datagemma-rig-27b-it.IQ4_NL.gguf GGUF IQ4_NL 14.56 GB Download
datagemma-rig-27b-it.IQ4_XS.gguf GGUF IQ4_XS 13.80 GB Download
datagemma-rig-27b-it.Q2_K.gguf GGUF Q2_K 9.73 GB Download
datagemma-rig-27b-it.Q2_K_S.gguf GGUF Q2_K_S 9.06 GB Download
datagemma-rig-27b-it.Q3_K.gguf GGUF Q3_K 12.50 GB Download
datagemma-rig-27b-it.Q3_K_L.gguf GGUF Q3_K_L 13.52 GB Download
datagemma-rig-27b-it.Q3_K_S.gguf GGUF Q3_K_S 11.33 GB Download
datagemma-rig-27b-it.Q4_K.gguf GGUF Q4_K 15.50 GB Download
datagemma-rig-27b-it.Q4_K_S.gguf GGUF Q4_K_S 14.66 GB Download
datagemma-rig-27b-it.Q5_K.gguf GGUF Q5_K 18.08 GB Download
datagemma-rig-27b-it.Q5_K_S.gguf GGUF Q5_K_S 17.59 GB Download
datagemma-rig-27b-it.Q6_K.gguf GGUF Q6_K 20.81 GB Download
datagemma-rig-27b-it.Q8_0.gguf GGUF 26.95 GB Download

Model Details Live

Model Slug
legraphista/datagemma-rig-27b-it-imat-gguf
Author
legraphista
Pipeline Task
text-generation
Library
gguf
Created
2024-09-12
Last Modified
2024-09-13
Gated
No
Private
No
HF SHA
8b7c29f2976023d38a982beb9dc0e100c6be4123
License
gemma
Language
Unknown
Base Model
google/datagemma-rig-27b-it

Metadata Inspector

Normalized metadata (stored in metadata_json)
{
  "metadata": {},
  "card_data": {
    "base_model": "google/datagemma-rig-27b-it",
    "extra_gated_button_content": "Acknowledge license",
    "extra_gated_heading": "Access Gemma on Hugging Face",
    "extra_gated_prompt": "To access Gemma on Hugging Face, you’re required to review and agree to Google’s usage license. To do this, please ensure you’re logged in to Hugging Face and click below. Requests are processed immediately.",
    "inference": false,
    "library_name": "gguf",
    "license": "gemma",
    "pipeline_tag": "text-generation",
    "quantized_by": "legraphista",
    "tags": [
      "conversational",
      "quantized",
      "GGUF",
      "quantization",
      "imat",
      "imatrix",
      "static",
      "16bit",
      "8bit",
      "6bit",
      "5bit",
      "4bit",
      "3bit",
      "2bit",
      "1bit"
    ],
    "frontmatter": {
      "base_model": "google/datagemma-rig-27b-it",
      "extra_gated_button_content": "Acknowledge license",
      "extra_gated_heading": "Access Gemma on Hugging Face",
      "extra_gated_prompt": "\"To access Gemma on Hugging Face, you\\u2019re required to review\\",
      "inference": "false",
      "library_name": "gguf",
      "license": "gemma",
      "pipeline_tag": "text-generation",
      "quantized_by": "legraphista",
      "tags": [
        "conversational",
        "quantized",
        "GGUF",
        "quantization",
        "imat",
        "imatrix",
        "static",
        "16bit",
        "8bit",
        "6bit",
        "5bit",
        "4bit",
        "3bit",
        "2bit",
        "1bit"
      ]
    },
    "hero_image_url": "",
    "summary": "_Llama.cpp imatrix quantization of google/datagemma-rig-27b-it_ Original Model: google/datagemma-rig-27b-it Original dtype: BF16 (bfloat16) Quantized by:  llama.cpp b3750 IMatrix dataset: here ---",
    "quick_links": [],
    "benchmark_table_html": "",
    "readme_markdown": "---\nbase_model: google/datagemma-rig-27b-it\nextra_gated_button_content: Acknowledge license\nextra_gated_heading: Access Gemma on Hugging Face\nextra_gated_prompt: \"To access Gemma on Hugging Face, you\\u2019re required to review\\\n  \\ and agree to Google\\u2019s usage license. To do this, please ensure you\\u2019\\\n  re logged in to Hugging Face and click below. Requests are processed immediately.\"\ninference: false\nlibrary_name: gguf\nlicense: gemma\npipeline_tag: text-generation\nquantized_by: legraphista\ntags:\n- conversational\n- quantized\n- GGUF\n- quantization\n- imat\n- imatrix\n- static\n- 16bit\n- 8bit\n- 6bit\n- 5bit\n- 4bit\n- 3bit\n- 2bit\n- 1bit\n---\n\n# datagemma-rig-27b-it-IMat-GGUF\n_Llama.cpp imatrix quantization of google/datagemma-rig-27b-it_\n\nOriginal Model: [google/datagemma-rig-27b-it](https://huggingface.co/google/datagemma-rig-27b-it)    \nOriginal dtype: `BF16` (`bfloat16`)  \nQuantized by:  llama.cpp [b3750](https://github.com/ggerganov/llama.cpp/releases/tag/b3750)  \nIMatrix dataset: [here](https://gist.githubusercontent.com/bartowski1182/eb213dccb3571f863da82e99418f81e8/raw/b2869d80f5c16fd7082594248e80144677736635/calibration_datav3.txt)  \n\n- [Files](#files)\n    - [IMatrix](#imatrix)\n    - [Common Quants](#common-quants)\n    - [All Quants](#all-quants)\n- [Downloading using huggingface-cli](#downloading-using-huggingface-cli)\n- [Inference](#inference)\n    - [Simple chat template](#simple-chat-template)\n    - [Llama.cpp](#llama-cpp)\n- [FAQ](#faq)\n    - [Why is the IMatrix not applied everywhere?](#why-is-the-imatrix-not-applied-everywhere)\n    - [How do I merge a split GGUF?](#how-do-i-merge-a-split-gguf)\n\n---\n\n## Files\n\n### IMatrix\nStatus: ✅ Available  \nLink: [here](https://huggingface.co/legraphista/datagemma-rig-27b-it-IMat-GGUF/blob/main/imatrix.dat)\n\n### Common Quants\n| Filename | Quant type | File Size | Status | Uses IMatrix | Is Split |\n| -------- | ---------- | --------- | ------ | ------------ | -------- |\n| [datagemma-rig-27b-it.Q8_0.gguf](https://huggingface.co/legraphista/datagemma-rig-27b-it-IMat-GGUF/blob/main/datagemma-rig-27b-it.Q8_0.gguf) | Q8_0 | 28.94GB | ✅ Available | ⚪ Static | 📦 No\n| [datagemma-rig-27b-it.Q6_K.gguf](https://huggingface.co/legraphista/datagemma-rig-27b-it-IMat-GGUF/blob/main/datagemma-rig-27b-it.Q6_K.gguf) | Q6_K | 22.34GB | ✅ Available | ⚪ Static | 📦 No\n| [datagemma-rig-27b-it.Q4_K.gguf](https://huggingface.co/legraphista/datagemma-rig-27b-it-IMat-GGUF/blob/main/datagemma-rig-27b-it.Q4_K.gguf) | Q4_K | 16.65GB | ✅ Available | 🟢 IMatrix | 📦 No\n| [datagemma-rig-27b-it.Q3_K.gguf](https://huggingface.co/legraphista/datagemma-rig-27b-it-IMat-GGUF/blob/main/datagemma-rig-27b-it.Q3_K.gguf) | Q3_K | 13.42GB | ✅ Available | 🟢 IMatrix | 📦 No\n| [datagemma-rig-27b-it.Q2_K.gguf](https://huggingface.co/legraphista/datagemma-rig-27b-it-IMat-GGUF/blob/main/datagemma-rig-27b-it.Q2_K.gguf) | Q2_K | 10.45GB | ✅ Available | 🟢 IMatrix | 📦 No\n\n\n### All Quants\n| Filename | Quant type | File Size | Status | Uses IMatrix | Is Split |\n| -------- | ---------- | --------- | ------ | ------------ | -------- |\n| [datagemma-rig-27b-it.BF16/*](https://huggingface.co/legraphista/datagemma-rig-27b-it-IMat-GGUF/tree/main/datagemma-rig-27b-it.BF16) | BF16 | 54.46GB | ✅ Available | ⚪ Static | ✂ Yes\n| [datagemma-rig-27b-it.FP16/*](https://huggingface.co/legraphista/datagemma-rig-27b-it-IMat-GGUF/tree/main/datagemma-rig-27b-it.FP16) | F16 | 54.46GB | ✅ Available | ⚪ Static | ✂ Yes\n| [datagemma-rig-27b-it.Q8_0.gguf](https://huggingface.co/legraphista/datagemma-rig-27b-it-IMat-GGUF/blob/main/datagemma-rig-27b-it.Q8_0.gguf) | Q8_0 | 28.94GB | ✅ Available | ⚪ Static | 📦 No\n| [datagemma-rig-27b-it.Q6_K.gguf](https://huggingface.co/legraphista/datagemma-rig-27b-it-IMat-GGUF/blob/main/datagemma-rig-27b-it.Q6_K.gguf) | Q6_K | 22.34GB | ✅ Available | ⚪ Static | 📦 No\n| [datagemma-rig-27b-it.Q5_K.gguf](https://huggingface.co/legraphista/datagemma-rig-27b-it-IMat-GGUF/blob/main/datagemma-rig-27b-it.Q5_K.gguf) | Q5_K | 19.41GB | ✅ Available | ⚪ Static | 📦 No\n| [datagemma-rig-27b-it.Q5_K_S.gguf](https://huggingface.co/legraphista/datagemma-rig-27b-it-IMat-GGUF/blob/main/datagemma-rig-27b-it.Q5_K_S.gguf) | Q5_K_S | 18.88GB | ✅ Available | ⚪ Static | 📦 No\n| [datagemma-rig-27b-it.Q4_K.gguf](https://huggingface.co/legraphista/datagemma-rig-27b-it-IMat-GGUF/blob/main/datagemma-rig-27b-it.Q4_K.gguf) | Q4_K | 16.65GB | ✅ Available | 🟢 IMatrix | 📦 No\n| [datagemma-rig-27b-it.Q4_K_S.gguf](https://huggingface.co/legraphista/datagemma-rig-27b-it-IMat-GGUF/blob/main/datagemma-rig-27b-it.Q4_K_S.gguf) | Q4_K_S | 15.74GB | ✅ Available | 🟢 IMatrix | 📦 No\n| [datagemma-rig-27b-it.IQ4_NL.gguf](https://huggingface.co/legraphista/datagemma-rig-27b-it-IMat-GGUF/blob/main/datagemma-rig-27b-it.IQ4_NL.gguf) | IQ4_NL | 15.63GB | ✅ Available | 🟢 IMatrix | 📦 No\n| [datagemma-rig-27b-it.IQ4_XS.gguf](https://huggingface.co/legraphista/datagemma-rig-27b-it-IMat-GGUF/blob/main/datagemma-rig-27b-it.IQ4_XS.gguf) | IQ4_XS | 14.81GB | ✅ Available | 🟢 IMatrix | 📦 No\n| [datagemma-rig-27b-it.Q3_K.gguf](https://huggingface.co/legraphista/datagemma-rig-27b-it-IMat-GGUF/blob/main/datagemma-rig-27b-it.Q3_K.gguf) | Q3_K | 13.42GB | ✅ Available | 🟢 IMatrix | 📦 No\n| [datagemma-rig-27b-it.Q3_K_L.gguf](https://huggingface.co/legraphista/datagemma-rig-27b-it-IMat-GGUF/blob/main/datagemma-rig-27b-it.Q3_K_L.gguf) | Q3_K_L | 14.52GB | ✅ Available | 🟢 IMatrix | 📦 No\n| [datagemma-rig-27b-it.Q3_K_S.gguf](https://huggingface.co/legraphista/datagemma-rig-27b-it-IMat-GGUF/blob/main/datagemma-rig-27b-it.Q3_K_S.gguf) | Q3_K_S | 12.17GB | ✅ Available | 🟢 IMatrix | 📦 No\n| [datagemma-rig-27b-it.IQ3_M.gguf](https://huggingface.co/legraphista/datagemma-rig-27b-it-IMat-GGUF/blob/main/datagemma-rig-27b-it.IQ3_M.gguf) | IQ3_M | 12.45GB | ✅ Available | 🟢 IMatrix | 📦 No\n| [datagemma-rig-27b-it.IQ3_S.gguf](https://huggingface.co/legraphista/datagemma-rig-27b-it-IMat-GGUF/blob/main/datagemma-rig-27b-it.IQ3_S.gguf) | IQ3_S | 12.17GB | ✅ Available | 🟢 IMatrix | 📦 No\n| [datagemma-rig-27b-it.IQ3_XS.gguf](https://huggingface.co/legraphista/datagemma-rig-27b-it-IMat-GGUF/blob/main/datagemma-rig-27b-it.IQ3_XS.gguf) | IQ3_XS | 11.55GB | ✅ Available | 🟢 IMatrix | 📦 No\n| [datagemma-rig-27b-it.IQ3_XXS.gguf](https://huggingface.co/legraphista/datagemma-rig-27b-it-IMat-GGUF/blob/main/datagemma-rig-27b-it.IQ3_XXS.gguf) | IQ3_XXS | 10.75GB | ✅ Available | 🟢 IMatrix | 📦 No\n| [datagemma-rig-27b-it.Q2_K.gguf](https://huggingface.co/legraphista/datagemma-rig-27b-it-IMat-GGUF/blob/main/datagemma-rig-27b-it.Q2_K.gguf) | Q2_K | 10.45GB | ✅ Available | 🟢 IMatrix | 📦 No\n| [datagemma-rig-27b-it.Q2_K_S.gguf](https://huggingface.co/legraphista/datagemma-rig-27b-it-IMat-GGUF/blob/main/datagemma-rig-27b-it.Q2_K_S.gguf) | Q2_K_S | 9.72GB | ✅ Available | 🟢 IMatrix | 📦 No\n| [datagemma-rig-27b-it.IQ2_M.gguf](https://huggingface.co/legraphista/datagemma-rig-27b-it-IMat-GGUF/blob/main/datagemma-rig-27b-it.IQ2_M.gguf) | IQ2_M | 9.40GB | ✅ Available | 🟢 IMatrix | 📦 No\n| [datagemma-rig-27b-it.IQ2_S.gguf](https://huggingface.co/legraphista/datagemma-rig-27b-it-IMat-GGUF/blob/main/datagemma-rig-27b-it.IQ2_S.gguf) | IQ2_S | 8.65GB | ✅ Available | 🟢 IMatrix | 📦 No\n| [datagemma-rig-27b-it.IQ2_XS.gguf](https://huggingface.co/legraphista/datagemma-rig-27b-it-IMat-GGUF/blob/main/datagemma-rig-27b-it.IQ2_XS.gguf) | IQ2_XS | 8.40GB | ✅ Available | 🟢 IMatrix | 📦 No\n| [datagemma-rig-27b-it.IQ2_XXS.gguf](https://huggingface.co/legraphista/datagemma-rig-27b-it-IMat-GGUF/blob/main/datagemma-rig-27b-it.IQ2_XXS.gguf) | IQ2_XXS | 7.63GB | ✅ Available | 🟢 IMatrix | 📦 No\n| [datagemma-rig-27b-it.IQ1_M.gguf](https://huggingface.co/legraphista/datagemma-rig-27b-it-IMat-GGUF/blob/main/datagemma-rig-27b-it.IQ1_M.gguf) | IQ1_M | 6.69GB | ✅ Available | 🟢 IMatrix | 📦 No\n| [datagemma-rig-27b-it.IQ1_S.gguf](https://huggingface.co/legraphista/datagemma-rig-27b-it-IMat-GGUF/blob/main/datagemma-rig-27b-it.IQ1_S.gguf) | IQ1_S | 6.13GB | ✅ Available | 🟢 IMatrix | 📦 No\n\n\n## Downloading using huggingface-cli\nIf you do not have hugginface-cli installed:\n```\npip install -U \"huggingface_hub[cli]\"\n```\nDownload the specific file you want:\n```\nhuggingface-cli download legraphista/datagemma-rig-27b-it-IMat-GGUF --include \"datagemma-rig-27b-it.Q8_0.gguf\" --local-dir ./\n```\nIf the model file is big, it has been split into multiple files. In order to download them all to a local folder, run:\n```\nhuggingface-cli download legraphista/datagemma-rig-27b-it-IMat-GGUF --include \"datagemma-rig-27b-it.Q8_0/*\" --local-dir ./\n# see FAQ for merging GGUF's\n```\n\n---\n\n## Inference\n\n### Simple chat template\n```\n<bos><start_of_turn>user\n{user_prompt}<end_of_turn>\n<start_of_turn>model\n{assistant_response}<end_of_turn>\n<start_of_turn>user\n{next_user_prompt}<end_of_turn>\n\n```\n\n### Llama.cpp\n```\nllama.cpp/main -m datagemma-rig-27b-it.Q8_0.gguf --color -i -p \"prompt here (according to the chat template)\"\n```\n\n---\n\n## FAQ\n\n### Why is the IMatrix not applied everywhere?\nAccording to [this investigation](https://www.reddit.com/r/LocalLLaMA/comments/1993iro/ggufs_quants_can_punch_above_their_weights_now/), it appears that lower quantizations are the only ones that benefit from the imatrix input (as per hellaswag results). \n\n### How do I merge a split GGUF?\n1. Make sure you have `gguf-split` available\n    - To get hold of `gguf-split`, navigate to https://github.com/ggerganov/llama.cpp/releases\n    - Download the appropriate zip for your system from the latest release\n    - Unzip the archive and you should be able to find `gguf-split`\n2. Locate your GGUF chunks folder (ex: `datagemma-rig-27b-it.Q8_0`)\n3. Run `gguf-split --merge datagemma-rig-27b-it.Q8_0/datagemma-rig-27b-it.Q8_0-00001-of-XXXXX.gguf datagemma-rig-27b-it.Q8_0.gguf`\n    - Make sure to point `gguf-split` to the first chunk of the split.\n\n---\n\nGot a suggestion? Ping me [@legraphista](https://x.com/legraphista)!",
    "related_quantizations": []
  },
  "tags": [
    "gguf",
    "conversational",
    "quantized",
    "GGUF",
    "quantization",
    "imat",
    "imatrix",
    "static",
    "16bit",
    "8bit",
    "6bit",
    "5bit",
    "4bit",
    "3bit",
    "2bit",
    "1bit",
    "text-generation",
    "base_model:google/datagemma-rig-27b-it",
    "base_model:quantized:google/datagemma-rig-27b-it",
    "license:gemma",
    "region:us"
  ],
  "likes": 0,
  "downloads": 256,
  "gated": false,
  "private": false,
  "last_modified": "2024-09-13T14:52:37.000Z",
  "created_at": "2024-09-12T16:59:53.000Z",
  "pipeline_tag": "text-generation",
  "library_name": "gguf"
}
Source payload excerpt (from Hugging Face API)
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