Model Intelligence Sheet
mradermacher/trotr-paraphrase-multilingual-minilm-l12-v2-gguf overview
About static quants of https://huggingface.co/FrancescoPeriti/TRoTR-paraphrase-multilingual-MiniLM-L12-v2 weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
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Repository Files & Downloads
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Direct downloads for all repository files
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| TRoTR-paraphrase-multilingual-MiniLM-L12-v2.IQ4_XS.gguf | GGUF | IQ4_XS | 202.07 MB | Download |
| TRoTR-paraphrase-multilingual-MiniLM-L12-v2.Q2_K.gguf | GGUF | Q2_K | 189.38 MB | Download |
| TRoTR-paraphrase-multilingual-MiniLM-L12-v2.Q3_K_L.gguf | GGUF | Q3_K_L | 203.93 MB | Download |
| TRoTR-paraphrase-multilingual-MiniLM-L12-v2.Q3_K_M.gguf | GGUF | Q3_K_M | 199.01 MB | Download |
| TRoTR-paraphrase-multilingual-MiniLM-L12-v2.Q3_K_S.gguf | GGUF | Q3_K_S | 193.49 MB | Download |
| TRoTR-paraphrase-multilingual-MiniLM-L12-v2.Q4_0_4_4.gguf | GGUF | — | 204.25 MB | Download |
| TRoTR-paraphrase-multilingual-MiniLM-L12-v2.Q4_K_M.gguf | GGUF | Q4_K_M | 208.60 MB | Download |
| TRoTR-paraphrase-multilingual-MiniLM-L12-v2.Q4_K_S.gguf | GGUF | Q4_K_S | 204.81 MB | Download |
| TRoTR-paraphrase-multilingual-MiniLM-L12-v2.Q5_K_M.gguf | GGUF | Q5_K_M | 216.62 MB | Download |
| TRoTR-paraphrase-multilingual-MiniLM-L12-v2.Q5_K_S.gguf | GGUF | Q5_K_S | 214.37 MB | Download |
| TRoTR-paraphrase-multilingual-MiniLM-L12-v2.Q6_K.gguf | GGUF | Q6_K | 225.13 MB | Download |
| TRoTR-paraphrase-multilingual-MiniLM-L12-v2.Q8_0.gguf | GGUF | — | 289.10 MB | Download |
| TRoTR-paraphrase-multilingual-MiniLM-L12-v2.f16.gguf | GGUF | F16 | 536.70 MB | Download |
Model Details Live
Metadata Inspector
Normalized metadata (stored in metadata_json)
{
"metadata": {},
"card_data": {
"base_model": "FrancescoPeriti/TRoTR-paraphrase-multilingual-MiniLM-L12-v2",
"datasets": [
"FrancescoPeriti/TRoTR"
],
"language": [
"en"
],
"library_name": "transformers",
"license": "cc-by-sa-4.0",
"quantized_by": "mradermacher",
"tags": [
"topic-relatedness",
"semantic-relatedness"
],
"frontmatter": {
"base_model": "FrancescoPeriti/TRoTR-paraphrase-multilingual-MiniLM-L12-v2",
"datasets": [
"FrancescoPeriti/TRoTR"
],
"language": [
"en"
],
"library_name": "transformers",
"license": "cc-by-sa-4.0",
"quantized_by": "mradermacher",
"tags": [
"topic-relatedness",
"semantic-relatedness"
]
},
"hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
"summary": "## About static quants of https://huggingface.co/FrancescoPeriti/TRoTR-paraphrase-multilingual-MiniLM-L12-v2 weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.",
"quick_links": [],
"benchmark_table_html": "",
"readme_markdown": "---\nbase_model: FrancescoPeriti/TRoTR-paraphrase-multilingual-MiniLM-L12-v2\ndatasets:\n- FrancescoPeriti/TRoTR\nlanguage:\n- en\nlibrary_name: transformers\nlicense: cc-by-sa-4.0\nquantized_by: mradermacher\ntags:\n- topic-relatedness\n- semantic-relatedness\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/FrancescoPeriti/TRoTR-paraphrase-multilingual-MiniLM-L12-v2\n\n<!-- provided-files -->\nweighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.\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/TRoTR-paraphrase-multilingual-MiniLM-L12-v2-GGUF/resolve/main/TRoTR-paraphrase-multilingual-MiniLM-L12-v2.Q2_K.gguf) | Q2_K | 0.3 | |\n| [GGUF](https://huggingface.co/mradermacher/TRoTR-paraphrase-multilingual-MiniLM-L12-v2-GGUF/resolve/main/TRoTR-paraphrase-multilingual-MiniLM-L12-v2.Q3_K_S.gguf) | Q3_K_S | 0.3 | |\n| [GGUF](https://huggingface.co/mradermacher/TRoTR-paraphrase-multilingual-MiniLM-L12-v2-GGUF/resolve/main/TRoTR-paraphrase-multilingual-MiniLM-L12-v2.Q3_K_M.gguf) | Q3_K_M | 0.3 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/TRoTR-paraphrase-multilingual-MiniLM-L12-v2-GGUF/resolve/main/TRoTR-paraphrase-multilingual-MiniLM-L12-v2.IQ4_XS.gguf) | IQ4_XS | 0.3 | |\n| [GGUF](https://huggingface.co/mradermacher/TRoTR-paraphrase-multilingual-MiniLM-L12-v2-GGUF/resolve/main/TRoTR-paraphrase-multilingual-MiniLM-L12-v2.Q3_K_L.gguf) | Q3_K_L | 0.3 | |\n| [GGUF](https://huggingface.co/mradermacher/TRoTR-paraphrase-multilingual-MiniLM-L12-v2-GGUF/resolve/main/TRoTR-paraphrase-multilingual-MiniLM-L12-v2.Q4_0_4_4.gguf) | Q4_0_4_4 | 0.3 | fast on arm, low quality |\n| [GGUF](https://huggingface.co/mradermacher/TRoTR-paraphrase-multilingual-MiniLM-L12-v2-GGUF/resolve/main/TRoTR-paraphrase-multilingual-MiniLM-L12-v2.Q4_K_S.gguf) | Q4_K_S | 0.3 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/TRoTR-paraphrase-multilingual-MiniLM-L12-v2-GGUF/resolve/main/TRoTR-paraphrase-multilingual-MiniLM-L12-v2.Q4_K_M.gguf) | Q4_K_M | 0.3 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/TRoTR-paraphrase-multilingual-MiniLM-L12-v2-GGUF/resolve/main/TRoTR-paraphrase-multilingual-MiniLM-L12-v2.Q5_K_S.gguf) | Q5_K_S | 0.3 | |\n| [GGUF](https://huggingface.co/mradermacher/TRoTR-paraphrase-multilingual-MiniLM-L12-v2-GGUF/resolve/main/TRoTR-paraphrase-multilingual-MiniLM-L12-v2.Q5_K_M.gguf) | Q5_K_M | 0.3 | |\n| [GGUF](https://huggingface.co/mradermacher/TRoTR-paraphrase-multilingual-MiniLM-L12-v2-GGUF/resolve/main/TRoTR-paraphrase-multilingual-MiniLM-L12-v2.Q6_K.gguf) | Q6_K | 0.3 | very good quality |\n| [GGUF](https://huggingface.co/mradermacher/TRoTR-paraphrase-multilingual-MiniLM-L12-v2-GGUF/resolve/main/TRoTR-paraphrase-multilingual-MiniLM-L12-v2.Q8_0.gguf) | Q8_0 | 0.4 | fast, best quality |\n| [GGUF](https://huggingface.co/mradermacher/TRoTR-paraphrase-multilingual-MiniLM-L12-v2-GGUF/resolve/main/TRoTR-paraphrase-multilingual-MiniLM-L12-v2.f16.gguf) | f16 | 0.7 | 16 bpw, overkill |\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",
"topic-relatedness",
"semantic-relatedness",
"en",
"dataset:FrancescoPeriti/TRoTR",
"base_model:FrancescoPeriti/TRoTR-paraphrase-multilingual-MiniLM-L12-v2",
"base_model:quantized:FrancescoPeriti/TRoTR-paraphrase-multilingual-MiniLM-L12-v2",
"license:cc-by-sa-4.0",
"endpoints_compatible",
"region:us",
"feature-extraction"
],
"likes": 0,
"downloads": 148,
"gated": false,
"private": false,
"last_modified": "2024-11-21T16:48:45.000Z",
"created_at": "2024-11-20T01:19:35.000Z",
"pipeline_tag": "",
"library_name": "transformers"
}
Source payload excerpt (from Hugging Face API)
{
"_id": "673d39273af47d1d2b7952aa",
"id": "mradermacher/TRoTR-paraphrase-multilingual-MiniLM-L12-v2-GGUF",
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"sha": "bb6a70997334cfc523b90b2da0e8ed4e2fd5be9e",
"createdAt": "2024-11-20T01:19:35.000Z",
"lastModified": "2024-11-21T16:48:45.000Z",
"author": "mradermacher",
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"siblings_count": 15
}