mradermacher/g2-xeno-simpo-27b-gguf Q6_K GGUF - Free GGUF Download is indexed on GraySoft with repository links, GGUF quant files, and Hugging Face metadata. This page helps you pick a local model for guIDE or other runtimes. See related models in the same shard below.
Model Intelligence Sheet
mradermacher/g2-xeno-simpo-27b-gguf overview
About static quants of https://huggingface.co/DazzlingXeno/G2-Xeno-SimPO-27b weighted/imatrix quants are available at https://huggingface.co/mradermacher/G2-Xeno-SimPO-27b-i1-GGUF
Downloads
374
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0
Pipeline
—
Library
transformers
Visibility
Public
Access
Open
Repository Files & Downloads
14 files detected
Direct downloads for all repository files
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| G2-Xeno-SimPO-27b.IQ3_M.gguf | GGUF | IQ3_M | 11.60 GB | Download |
| G2-Xeno-SimPO-27b.IQ3_S.gguf | GGUF | IQ3_S | 11.33 GB | Download |
| G2-Xeno-SimPO-27b.IQ3_XS.gguf | GGUF | IQ3_XS | 10.76 GB | Download |
| G2-Xeno-SimPO-27b.IQ4_XS.gguf | GGUF | IQ4_XS | 13.92 GB | Download |
| G2-Xeno-SimPO-27b.Q2_K.gguf | GGUF | Q2_K | 9.73 GB | Download |
| G2-Xeno-SimPO-27b.Q3_K_L.gguf | GGUF | Q3_K_L | 13.52 GB | Download |
| G2-Xeno-SimPO-27b.Q3_K_M.gguf | GGUF | Q3_K_M | 12.50 GB | Download |
| G2-Xeno-SimPO-27b.Q3_K_S.gguf | GGUF | Q3_K_S | 11.33 GB | Download |
| G2-Xeno-SimPO-27b.Q4_K_M.gguf | GGUF | Q4_K_M | 15.50 GB | Download |
| G2-Xeno-SimPO-27b.Q4_K_S.gguf | GGUF | Q4_K_S | 14.66 GB | Download |
| G2-Xeno-SimPO-27b.Q5_K_M.gguf | GGUF | Q5_K_M | 18.08 GB | Download |
| G2-Xeno-SimPO-27b.Q5_K_S.gguf | GGUF | Q5_K_S | 17.59 GB | Download |
| G2-Xeno-SimPO-27b.Q6_K.gguf | GGUF | Q6_K | 20.81 GB | Download |
| G2-Xeno-SimPO-27b.Q8_0.gguf | GGUF | — | 26.95 GB | Download |
Model Details Live
Metadata Inspector
Normalized metadata (stored in metadata_json)
{
"metadata": {},
"card_data": {
"base_model": "DazzlingXeno/G2-Xeno-SimPO-27b",
"language": [
"en"
],
"library_name": "transformers",
"quantized_by": "mradermacher",
"tags": [
"Story Telling",
"Creative Writing",
"GutenBerg",
"Gemma",
"Prose"
],
"frontmatter": {
"base_model": "DazzlingXeno/G2-Xeno-SimPO-27b",
"language": [
"en"
],
"library_name": "transformers",
"quantized_by": "mradermacher",
"tags": [
"Story Telling",
"Creative Writing",
"GutenBerg",
"Gemma",
"Prose"
]
},
"hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
"summary": "## About static quants of https://huggingface.co/DazzlingXeno/G2-Xeno-SimPO-27b weighted/imatrix quants are available at https://huggingface.co/mradermacher/G2-Xeno-SimPO-27b-i1-GGUF",
"quick_links": [],
"benchmark_table_html": "",
"readme_markdown": "---\nbase_model: DazzlingXeno/G2-Xeno-SimPO-27b\nlanguage:\n- en\nlibrary_name: transformers\nquantized_by: mradermacher\ntags:\n- Story Telling\n- Creative Writing\n- GutenBerg\n- Gemma\n- Prose\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/DazzlingXeno/G2-Xeno-SimPO-27b\n\n<!-- provided-files -->\nweighted/imatrix quants are available at https://huggingface.co/mradermacher/G2-Xeno-SimPO-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/G2-Xeno-SimPO-27b-GGUF/resolve/main/G2-Xeno-SimPO-27b.Q2_K.gguf) | Q2_K | 10.5 | |\n| [GGUF](https://huggingface.co/mradermacher/G2-Xeno-SimPO-27b-GGUF/resolve/main/G2-Xeno-SimPO-27b.IQ3_XS.gguf) | IQ3_XS | 11.7 | |\n| [GGUF](https://huggingface.co/mradermacher/G2-Xeno-SimPO-27b-GGUF/resolve/main/G2-Xeno-SimPO-27b.IQ3_S.gguf) | IQ3_S | 12.3 | beats Q3_K* |\n| [GGUF](https://huggingface.co/mradermacher/G2-Xeno-SimPO-27b-GGUF/resolve/main/G2-Xeno-SimPO-27b.Q3_K_S.gguf) | Q3_K_S | 12.3 | |\n| [GGUF](https://huggingface.co/mradermacher/G2-Xeno-SimPO-27b-GGUF/resolve/main/G2-Xeno-SimPO-27b.IQ3_M.gguf) | IQ3_M | 12.6 | |\n| [GGUF](https://huggingface.co/mradermacher/G2-Xeno-SimPO-27b-GGUF/resolve/main/G2-Xeno-SimPO-27b.Q3_K_M.gguf) | Q3_K_M | 13.5 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/G2-Xeno-SimPO-27b-GGUF/resolve/main/G2-Xeno-SimPO-27b.Q3_K_L.gguf) | Q3_K_L | 14.6 | |\n| [GGUF](https://huggingface.co/mradermacher/G2-Xeno-SimPO-27b-GGUF/resolve/main/G2-Xeno-SimPO-27b.IQ4_XS.gguf) | IQ4_XS | 15.0 | |\n| [GGUF](https://huggingface.co/mradermacher/G2-Xeno-SimPO-27b-GGUF/resolve/main/G2-Xeno-SimPO-27b.Q4_K_S.gguf) | Q4_K_S | 15.8 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/G2-Xeno-SimPO-27b-GGUF/resolve/main/G2-Xeno-SimPO-27b.Q4_K_M.gguf) | Q4_K_M | 16.7 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/G2-Xeno-SimPO-27b-GGUF/resolve/main/G2-Xeno-SimPO-27b.Q5_K_S.gguf) | Q5_K_S | 19.0 | |\n| [GGUF](https://huggingface.co/mradermacher/G2-Xeno-SimPO-27b-GGUF/resolve/main/G2-Xeno-SimPO-27b.Q5_K_M.gguf) | Q5_K_M | 19.5 | |\n| [GGUF](https://huggingface.co/mradermacher/G2-Xeno-SimPO-27b-GGUF/resolve/main/G2-Xeno-SimPO-27b.Q6_K.gguf) | Q6_K | 22.4 | very good quality |\n| [GGUF](https://huggingface.co/mradermacher/G2-Xeno-SimPO-27b-GGUF/resolve/main/G2-Xeno-SimPO-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\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",
"Story Telling",
"Creative Writing",
"GutenBerg",
"Gemma",
"Prose",
"en",
"base_model:DazzlingXeno/G2-Xeno-SimPO-27b",
"base_model:quantized:DazzlingXeno/G2-Xeno-SimPO-27b",
"endpoints_compatible",
"region:us",
"conversational"
],
"likes": 0,
"downloads": 374,
"gated": false,
"private": false,
"last_modified": "2024-09-26T12:45:50.000Z",
"created_at": "2024-09-24T19:20:16.000Z",
"pipeline_tag": "",
"library_name": "transformers"
}
Source payload excerpt (from Hugging Face API)
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"createdAt": "2024-09-24T19:20:16.000Z",
"lastModified": "2024-09-26T12:45:50.000Z",
"author": "mradermacher",
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