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mradermacher/gemma4-alpaca-uncensored-i1-gguf overview

About weighted/imatrix quants of https://huggingface.co/renierd6/gemma4-alpaca-uncensored For a convenient overview and download list, visit our model page for this model. static quants are available at https://huggingface.co/mradermacher/gemma4-alpaca-uncensored-GGUF This is a vision model - mmproj files (if any) will be in the static repository.

transformersgguftext-generation-inferenceunslothgemma4enbase_model:renierd6/gemma4-alpaca-uncensoredbase_model:quantized:renierd6/gemma4-alpaca-uncensoredlicense:apache-2.0endpoints_compatibleregion:usimatrixconversational
mradermacher/gemma4-alpaca-uncensored-i1-gguf visual
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1,705
Likes
0
Pipeline
Library
transformers
Visibility
Public
Access
Open

Repository Files & Downloads

16 files detected
Direct downloads for all repository files
FileTypeQuantizationSizeLink
gemma4-alpaca-uncensored.i1-IQ3_M.gguf GGUF IQ3_M 2.92 GB Download
gemma4-alpaca-uncensored.i1-IQ3_S.gguf GGUF IQ3_S 2.90 GB Download
gemma4-alpaca-uncensored.i1-IQ4_NL.gguf GGUF IQ4_NL 3.13 GB Download
gemma4-alpaca-uncensored.i1-IQ4_XS.gguf GGUF IQ4_XS 3.08 GB Download
gemma4-alpaca-uncensored.i1-Q2_K.gguf GGUF Q2_K 2.78 GB Download
gemma4-alpaca-uncensored.i1-Q3_K_L.gguf GGUF Q3_K_L 3.06 GB Download
gemma4-alpaca-uncensored.i1-Q3_K_M.gguf GGUF Q3_K_M 2.98 GB Download
gemma4-alpaca-uncensored.i1-Q3_K_S.gguf GGUF Q3_K_S 2.90 GB Download
gemma4-alpaca-uncensored.i1-Q4_0.gguf GGUF 3.13 GB Download
gemma4-alpaca-uncensored.i1-Q4_1.gguf GGUF 3.24 GB Download
gemma4-alpaca-uncensored.i1-Q4_K_M.gguf GGUF Q4_K_M 3.19 GB Download
gemma4-alpaca-uncensored.i1-Q4_K_S.gguf GGUF Q4_K_S 3.13 GB Download
gemma4-alpaca-uncensored.i1-Q5_K_M.gguf GGUF Q5_K_M 3.38 GB Download
gemma4-alpaca-uncensored.i1-Q5_K_S.gguf GGUF Q5_K_S 3.35 GB Download
gemma4-alpaca-uncensored.i1-Q6_K.gguf GGUF Q6_K 3.58 GB Download
gemma4-alpaca-uncensored.imatrix.gguf GGUF 2.69 MB Download

Model Details Live

Model Slug
mradermacher/gemma4-alpaca-uncensored-i1-gguf
Author
mradermacher
Pipeline Task
Library
transformers
Created
2026-04-14
Last Modified
2026-04-14
Gated
No
Private
No
HF SHA
2ac9aef103739e7864478728608521c7291034b4
License
apache-2.0
Language
en
Base Model
renierd6/gemma4-alpaca-uncensored

Metadata Inspector

Normalized metadata (stored in metadata_json)
{
  "metadata": {},
  "card_data": {
    "base_model": "renierd6/gemma4-alpaca-uncensored",
    "language": [
      "en"
    ],
    "library_name": "transformers",
    "license": "apache-2.0",
    "mradermacher": {
      "readme_rev": 1
    },
    "quantized_by": "mradermacher",
    "tags": [
      "text-generation-inference",
      "transformers",
      "unsloth",
      "gemma4"
    ],
    "frontmatter": {
      "base_model": "renierd6/gemma4-alpaca-uncensored",
      "language": [
        "en"
      ],
      "library_name": "transformers",
      "license": "apache-2.0",
      "mradermacher": [],
      "quantized_by": "mradermacher",
      "tags": [
        "text-generation-inference",
        "transformers",
        "unsloth",
        "gemma4"
      ]
    },
    "hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
    "summary": "## About         weighted/imatrix quants of https://huggingface.co/renierd6/gemma4-alpaca-uncensored  ***For a convenient overview and download list, visit our model page for this model.*** static quants are available at https://huggingface.co/mradermacher/gemma4-alpaca-uncensored-GGUF **This is a vision model - mmproj files (if any) will be in the static repository.**",
    "quick_links": [],
    "benchmark_table_html": "",
    "readme_markdown": "---\nbase_model: renierd6/gemma4-alpaca-uncensored\nlanguage:\n- en\nlibrary_name: transformers\nlicense: apache-2.0\nmradermacher:\n  readme_rev: 1\nquantized_by: mradermacher\ntags:\n- text-generation-inference\n- transformers\n- unsloth\n- gemma4\n---\n## About\n\n<!-- ### quantize_version: 2 -->\n<!-- ### output_tensor_quantised: 1 -->\n<!-- ### convert_type: hf -->\n<!-- ### vocab_type:  -->\n<!-- ### tags: nicoboss -->\n<!-- ### quants:  Q2_K IQ3_M Q4_K_S IQ3_XXS Q3_K_M small-IQ4_NL Q4_K_M IQ2_M Q6_K IQ4_XS Q2_K_S IQ1_M Q3_K_S IQ2_XXS Q3_K_L IQ2_XS Q5_K_S IQ2_S IQ1_S Q5_K_M Q4_0 IQ3_XS Q4_1 IQ3_S -->\n<!-- ### quants_skip:  -->\n<!-- ### skip_mmproj:  -->\nweighted/imatrix quants of https://huggingface.co/renierd6/gemma4-alpaca-uncensored\n\n<!-- provided-files -->\n\n***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#gemma4-alpaca-uncensored-i1-GGUF).***\n\nstatic quants are available at https://huggingface.co/mradermacher/gemma4-alpaca-uncensored-GGUF\n\n**This is a vision model - mmproj files (if any) will be in the [static repository](https://huggingface.co/mradermacher/gemma4-alpaca-uncensored-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/gemma4-alpaca-uncensored-i1-GGUF/resolve/main/gemma4-alpaca-uncensored.imatrix.gguf) | imatrix | 0.1 | imatrix file (for creating your own quants) |\n| [GGUF](https://huggingface.co/mradermacher/gemma4-alpaca-uncensored-i1-GGUF/resolve/main/gemma4-alpaca-uncensored.i1-Q2_K.gguf) | i1-Q2_K | 3.1 | IQ3_XXS probably better |\n| [GGUF](https://huggingface.co/mradermacher/gemma4-alpaca-uncensored-i1-GGUF/resolve/main/gemma4-alpaca-uncensored.i1-Q3_K_S.gguf) | i1-Q3_K_S | 3.2 | IQ3_XS probably better |\n| [GGUF](https://huggingface.co/mradermacher/gemma4-alpaca-uncensored-i1-GGUF/resolve/main/gemma4-alpaca-uncensored.i1-IQ3_S.gguf) | i1-IQ3_S | 3.2 | beats Q3_K* |\n| [GGUF](https://huggingface.co/mradermacher/gemma4-alpaca-uncensored-i1-GGUF/resolve/main/gemma4-alpaca-uncensored.i1-IQ3_M.gguf) | i1-IQ3_M | 3.2 |  |\n| [GGUF](https://huggingface.co/mradermacher/gemma4-alpaca-uncensored-i1-GGUF/resolve/main/gemma4-alpaca-uncensored.i1-Q3_K_M.gguf) | i1-Q3_K_M | 3.3 | IQ3_S probably better |\n| [GGUF](https://huggingface.co/mradermacher/gemma4-alpaca-uncensored-i1-GGUF/resolve/main/gemma4-alpaca-uncensored.i1-Q3_K_L.gguf) | i1-Q3_K_L | 3.4 | IQ3_M probably better |\n| [GGUF](https://huggingface.co/mradermacher/gemma4-alpaca-uncensored-i1-GGUF/resolve/main/gemma4-alpaca-uncensored.i1-IQ4_XS.gguf) | i1-IQ4_XS | 3.4 |  |\n| [GGUF](https://huggingface.co/mradermacher/gemma4-alpaca-uncensored-i1-GGUF/resolve/main/gemma4-alpaca-uncensored.i1-IQ4_NL.gguf) | i1-IQ4_NL | 3.5 | prefer IQ4_XS |\n| [GGUF](https://huggingface.co/mradermacher/gemma4-alpaca-uncensored-i1-GGUF/resolve/main/gemma4-alpaca-uncensored.i1-Q4_0.gguf) | i1-Q4_0 | 3.5 | fast, low quality |\n| [GGUF](https://huggingface.co/mradermacher/gemma4-alpaca-uncensored-i1-GGUF/resolve/main/gemma4-alpaca-uncensored.i1-Q4_K_S.gguf) | i1-Q4_K_S | 3.5 | optimal size/speed/quality |\n| [GGUF](https://huggingface.co/mradermacher/gemma4-alpaca-uncensored-i1-GGUF/resolve/main/gemma4-alpaca-uncensored.i1-Q4_K_M.gguf) | i1-Q4_K_M | 3.5 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/gemma4-alpaca-uncensored-i1-GGUF/resolve/main/gemma4-alpaca-uncensored.i1-Q4_1.gguf) | i1-Q4_1 | 3.6 |  |\n| [GGUF](https://huggingface.co/mradermacher/gemma4-alpaca-uncensored-i1-GGUF/resolve/main/gemma4-alpaca-uncensored.i1-Q5_K_S.gguf) | i1-Q5_K_S | 3.7 |  |\n| [GGUF](https://huggingface.co/mradermacher/gemma4-alpaca-uncensored-i1-GGUF/resolve/main/gemma4-alpaca-uncensored.i1-Q5_K_M.gguf) | i1-Q5_K_M | 3.7 |  |\n| [GGUF](https://huggingface.co/mradermacher/gemma4-alpaca-uncensored-i1-GGUF/resolve/main/gemma4-alpaca-uncensored.i1-Q6_K.gguf) | i1-Q6_K | 3.9 | practically like static Q6_K |\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",
    "text-generation-inference",
    "unsloth",
    "gemma4",
    "en",
    "base_model:renierd6/gemma4-alpaca-uncensored",
    "base_model:quantized:renierd6/gemma4-alpaca-uncensored",
    "license:apache-2.0",
    "endpoints_compatible",
    "region:us",
    "imatrix",
    "conversational"
  ],
  "likes": 0,
  "downloads": 1705,
  "gated": false,
  "private": false,
  "last_modified": "2026-04-14T14:27:21.000Z",
  "created_at": "2026-04-14T12:51:24.000Z",
  "pipeline_tag": "",
  "library_name": "transformers"
}
Source payload excerpt (from Hugging Face API)
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