Model Intelligence Sheet
mradermacher/wingpt-babel-2.1-i1-gguf overview
About weighted/imatrix quants of https://huggingface.co/winninghealth/WiNGPT-Babel-2.1 For a convenient overview and download list, visit our model page for this model. static quants are available at https://huggingface.co/mradermacher/WiNGPT-Babel-2.1-GGUF
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transformers
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Repository Files & Downloads
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Direct downloads for all repository files
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| WiNGPT-Babel-2.1.i1-IQ1_M.gguf | GGUF | IQ1_M | 518.60 MB | Download |
| WiNGPT-Babel-2.1.i1-IQ1_S.gguf | GGUF | IQ1_S | 491.88 MB | Download |
| WiNGPT-Babel-2.1.i1-IQ2_M.gguf | GGUF | IQ2_M | 662.97 MB | Download |
| WiNGPT-Babel-2.1.i1-IQ2_S.gguf | GGUF | IQ2_S | 627.35 MB | Download |
| WiNGPT-Babel-2.1.i1-IQ2_XS.gguf | GGUF | IQ2_XS | 602.26 MB | Download |
| WiNGPT-Babel-2.1.i1-IQ2_XXS.gguf | GGUF | IQ2_XXS | 563.13 MB | Download |
| WiNGPT-Babel-2.1.i1-IQ3_M.gguf | GGUF | IQ3_M | 854.17 MB | Download |
| WiNGPT-Babel-2.1.i1-IQ3_S.gguf | GGUF | IQ3_S | 827.07 MB | Download |
| WiNGPT-Babel-2.1.i1-IQ3_XS.gguf | GGUF | IQ3_XS | 795.57 MB | Download |
| WiNGPT-Babel-2.1.i1-IQ3_XXS.gguf | GGUF | IQ3_XXS | 719.41 MB | Download |
| WiNGPT-Babel-2.1.i1-IQ4_NL.gguf | GGUF | IQ4_NL | 1005.57 MB | Download |
| WiNGPT-Babel-2.1.i1-IQ4_XS.gguf | GGUF | IQ4_XS | 963.57 MB | Download |
| WiNGPT-Babel-2.1.i1-Q2_K.gguf | GGUF | Q2_K | 741.76 MB | Download |
| WiNGPT-Babel-2.1.i1-Q2_K_S.gguf | GGUF | Q2_K_S | 699.01 MB | Download |
| WiNGPT-Babel-2.1.i1-Q3_K_L.gguf | GGUF | Q3_K_L | 957.01 MB | Download |
| WiNGPT-Babel-2.1.i1-Q3_K_M.gguf | GGUF | Q3_K_M | 896.01 MB | Download |
| WiNGPT-Babel-2.1.i1-Q3_K_S.gguf | GGUF | Q3_K_S | 827.07 MB | Download |
| WiNGPT-Babel-2.1.i1-Q4_0.gguf | GGUF | — | 1007.82 MB | Download |
| WiNGPT-Babel-2.1.i1-Q4_1.gguf | GGUF | — | 1.06 GB | Download |
| WiNGPT-Babel-2.1.i1-Q4_K_M.gguf | GGUF | Q4_K_M | 1.03 GB | Download |
| WiNGPT-Babel-2.1.i1-Q4_K_S.gguf | GGUF | Q4_K_S | 1011.07 MB | Download |
| WiNGPT-Babel-2.1.i1-Q5_K_M.gguf | GGUF | Q5_K_M | 1.17 GB | Download |
| WiNGPT-Babel-2.1.i1-Q5_K_S.gguf | GGUF | Q5_K_S | 1.15 GB | Download |
| WiNGPT-Babel-2.1.i1-Q6_K.gguf | GGUF | Q6_K | 1.32 GB | Download |
| WiNGPT-Babel-2.1.imatrix.gguf | GGUF | — | 2.00 MB | Download |
Model Details Live
Metadata Inspector
Normalized metadata (stored in metadata_json)
{
"metadata": {},
"card_data": {
"base_model": "winninghealth/WiNGPT-Babel-2.1",
"datasets": [
"google/wmt24pp"
],
"language": [
"ar",
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"library_name": "transformers",
"license": "apache-2.0",
"mradermacher": {
"readme_rev": 1
},
"quantized_by": "mradermacher",
"frontmatter": {
"base_model": "winninghealth/WiNGPT-Babel-2.1",
"datasets": [
"google/wmt24pp"
],
"language": [
"ar",
"bg",
"bn",
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"hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
"summary": "## About weighted/imatrix quants of https://huggingface.co/winninghealth/WiNGPT-Babel-2.1 ***For a convenient overview and download list, visit our model page for this model.*** static quants are available at https://huggingface.co/mradermacher/WiNGPT-Babel-2.1-GGUF",
"quick_links": [],
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"readme_markdown": "---\nbase_model: winninghealth/WiNGPT-Babel-2.1\ndatasets:\n- google/wmt24pp\nlanguage:\n- ar\n- bg\n- bn\n- ca\n- cs\n- da\n- de\n- el\n- es\n- et\n- fa\n- fi\n- fil\n- fr\n- gu\n- he\n- hi\n- hr\n- hu\n- id\n- is\n- it\n- ja\n- kn\n- ko\n- lt\n- lv\n- ml\n- mr\n- nl\n- no\n- pa\n- pl\n- pt\n- ro\n- ru\n- sk\n- sl\n- sr\n- sv\n- sw\n- ta\n- te\n- th\n- tr\n- uk\n- ur\n- vi\n- zh\n- zu\nlibrary_name: transformers\nlicense: apache-2.0\nmradermacher:\n readme_rev: 1\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: 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/winninghealth/WiNGPT-Babel-2.1\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#WiNGPT-Babel-2.1-i1-GGUF).***\n\nstatic quants are available at https://huggingface.co/mradermacher/WiNGPT-Babel-2.1-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/WiNGPT-Babel-2.1-i1-GGUF/resolve/main/WiNGPT-Babel-2.1.imatrix.gguf) | imatrix | 0.1 | imatrix file (for creating your own quants) |\n| [GGUF](https://huggingface.co/mradermacher/WiNGPT-Babel-2.1-i1-GGUF/resolve/main/WiNGPT-Babel-2.1.i1-IQ1_S.gguf) | i1-IQ1_S | 0.6 | for the desperate |\n| [GGUF](https://huggingface.co/mradermacher/WiNGPT-Babel-2.1-i1-GGUF/resolve/main/WiNGPT-Babel-2.1.i1-IQ1_M.gguf) | i1-IQ1_M | 0.6 | mostly desperate |\n| [GGUF](https://huggingface.co/mradermacher/WiNGPT-Babel-2.1-i1-GGUF/resolve/main/WiNGPT-Babel-2.1.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 0.7 | |\n| [GGUF](https://huggingface.co/mradermacher/WiNGPT-Babel-2.1-i1-GGUF/resolve/main/WiNGPT-Babel-2.1.i1-IQ2_XS.gguf) | i1-IQ2_XS | 0.7 | |\n| [GGUF](https://huggingface.co/mradermacher/WiNGPT-Babel-2.1-i1-GGUF/resolve/main/WiNGPT-Babel-2.1.i1-IQ2_S.gguf) | i1-IQ2_S | 0.8 | |\n| [GGUF](https://huggingface.co/mradermacher/WiNGPT-Babel-2.1-i1-GGUF/resolve/main/WiNGPT-Babel-2.1.i1-IQ2_M.gguf) | i1-IQ2_M | 0.8 | |\n| [GGUF](https://huggingface.co/mradermacher/WiNGPT-Babel-2.1-i1-GGUF/resolve/main/WiNGPT-Babel-2.1.i1-Q2_K_S.gguf) | i1-Q2_K_S | 0.8 | very low quality |\n| [GGUF](https://huggingface.co/mradermacher/WiNGPT-Babel-2.1-i1-GGUF/resolve/main/WiNGPT-Babel-2.1.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 0.9 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/WiNGPT-Babel-2.1-i1-GGUF/resolve/main/WiNGPT-Babel-2.1.i1-Q2_K.gguf) | i1-Q2_K | 0.9 | IQ3_XXS probably better |\n| [GGUF](https://huggingface.co/mradermacher/WiNGPT-Babel-2.1-i1-GGUF/resolve/main/WiNGPT-Babel-2.1.i1-IQ3_XS.gguf) | i1-IQ3_XS | 0.9 | |\n| [GGUF](https://huggingface.co/mradermacher/WiNGPT-Babel-2.1-i1-GGUF/resolve/main/WiNGPT-Babel-2.1.i1-IQ3_S.gguf) | i1-IQ3_S | 1.0 | beats Q3_K* |\n| [GGUF](https://huggingface.co/mradermacher/WiNGPT-Babel-2.1-i1-GGUF/resolve/main/WiNGPT-Babel-2.1.i1-Q3_K_S.gguf) | i1-Q3_K_S | 1.0 | IQ3_XS probably better |\n| [GGUF](https://huggingface.co/mradermacher/WiNGPT-Babel-2.1-i1-GGUF/resolve/main/WiNGPT-Babel-2.1.i1-IQ3_M.gguf) | i1-IQ3_M | 1.0 | |\n| [GGUF](https://huggingface.co/mradermacher/WiNGPT-Babel-2.1-i1-GGUF/resolve/main/WiNGPT-Babel-2.1.i1-Q3_K_M.gguf) | i1-Q3_K_M | 1.0 | IQ3_S probably better |\n| [GGUF](https://huggingface.co/mradermacher/WiNGPT-Babel-2.1-i1-GGUF/resolve/main/WiNGPT-Babel-2.1.i1-Q3_K_L.gguf) | i1-Q3_K_L | 1.1 | IQ3_M probably better |\n| [GGUF](https://huggingface.co/mradermacher/WiNGPT-Babel-2.1-i1-GGUF/resolve/main/WiNGPT-Babel-2.1.i1-IQ4_XS.gguf) | i1-IQ4_XS | 1.1 | |\n| [GGUF](https://huggingface.co/mradermacher/WiNGPT-Babel-2.1-i1-GGUF/resolve/main/WiNGPT-Babel-2.1.i1-IQ4_NL.gguf) | i1-IQ4_NL | 1.2 | prefer IQ4_XS |\n| [GGUF](https://huggingface.co/mradermacher/WiNGPT-Babel-2.1-i1-GGUF/resolve/main/WiNGPT-Babel-2.1.i1-Q4_0.gguf) | i1-Q4_0 | 1.2 | fast, low quality |\n| [GGUF](https://huggingface.co/mradermacher/WiNGPT-Babel-2.1-i1-GGUF/resolve/main/WiNGPT-Babel-2.1.i1-Q4_K_S.gguf) | i1-Q4_K_S | 1.2 | optimal size/speed/quality |\n| [GGUF](https://huggingface.co/mradermacher/WiNGPT-Babel-2.1-i1-GGUF/resolve/main/WiNGPT-Babel-2.1.i1-Q4_K_M.gguf) | i1-Q4_K_M | 1.2 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/WiNGPT-Babel-2.1-i1-GGUF/resolve/main/WiNGPT-Babel-2.1.i1-Q4_1.gguf) | i1-Q4_1 | 1.2 | |\n| [GGUF](https://huggingface.co/mradermacher/WiNGPT-Babel-2.1-i1-GGUF/resolve/main/WiNGPT-Babel-2.1.i1-Q5_K_S.gguf) | i1-Q5_K_S | 1.3 | |\n| [GGUF](https://huggingface.co/mradermacher/WiNGPT-Babel-2.1-i1-GGUF/resolve/main/WiNGPT-Babel-2.1.i1-Q5_K_M.gguf) | i1-Q5_K_M | 1.4 | |\n| [GGUF](https://huggingface.co/mradermacher/WiNGPT-Babel-2.1-i1-GGUF/resolve/main/WiNGPT-Babel-2.1.i1-Q6_K.gguf) | i1-Q6_K | 1.5 | practically like static Q6_K |\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. 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": [
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"dataset:google/wmt24pp",
"base_model:winninghealth/WiNGPT-Babel-2.1",
"base_model:quantized:winninghealth/WiNGPT-Babel-2.1",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
],
"likes": 1,
"downloads": 107,
"gated": false,
"private": false,
"last_modified": "2025-12-07T01:45:00.000Z",
"created_at": "2025-11-15T21:04:06.000Z",
"pipeline_tag": "",
"library_name": "transformers"
}
Source payload excerpt (from Hugging Face API)
{
"_id": "6918eac619c6c652976a5dbe",
"id": "mradermacher/WiNGPT-Babel-2.1-i1-GGUF",
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"sha": "3dd3699143b9e0a91f4f67cd8ed05d9aad2550c1",
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"author": "mradermacher",
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