Model Intelligence Sheet
mradermacher/una-thepitbull-21.4b-v2-i1-gguf overview
About weighted/imatrix quants of https://huggingface.co/fblgit/UNA-ThePitbull-21.4B-v2 static quants are available at https://huggingface.co/mradermacher/UNA-ThePitbull-21.4B-v2-GGUF
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transformers
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Repository Files & Downloads
21 files detected
Direct downloads for all repository files
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| UNA-ThePitbull-21.4B-v2.i1-IQ1_M.gguf | GGUF | IQ1_M | 4.91 GB | Download |
| UNA-ThePitbull-21.4B-v2.i1-IQ1_S.gguf | GGUF | IQ1_S | 4.53 GB | Download |
| UNA-ThePitbull-21.4B-v2.i1-IQ2_M.gguf | GGUF | IQ2_M | 6.98 GB | Download |
| UNA-ThePitbull-21.4B-v2.i1-IQ2_S.gguf | GGUF | IQ2_S | 6.48 GB | Download |
| UNA-ThePitbull-21.4B-v2.i1-IQ2_XS.gguf | GGUF | IQ2_XS | 6.11 GB | Download |
| UNA-ThePitbull-21.4B-v2.i1-IQ2_XXS.gguf | GGUF | IQ2_XXS | 5.54 GB | Download |
| UNA-ThePitbull-21.4B-v2.i1-IQ3_M.gguf | GGUF | IQ3_M | 9.14 GB | Download |
| UNA-ThePitbull-21.4B-v2.i1-IQ3_S.gguf | GGUF | IQ3_S | 8.82 GB | Download |
| UNA-ThePitbull-21.4B-v2.i1-IQ3_XS.gguf | GGUF | IQ3_XS | 8.38 GB | Download |
| UNA-ThePitbull-21.4B-v2.i1-IQ3_XXS.gguf | GGUF | IQ3_XXS | 7.83 GB | Download |
| UNA-ThePitbull-21.4B-v2.i1-IQ4_XS.gguf | GGUF | IQ4_XS | 10.80 GB | Download |
| UNA-ThePitbull-21.4B-v2.i1-Q2_K.gguf | GGUF | Q2_K | 7.56 GB | Download |
| UNA-ThePitbull-21.4B-v2.i1-Q3_K_L.gguf | GGUF | Q3_K_L | 10.59 GB | Download |
| UNA-ThePitbull-21.4B-v2.i1-Q3_K_M.gguf | GGUF | Q3_K_M | 9.75 GB | Download |
| UNA-ThePitbull-21.4B-v2.i1-Q3_K_S.gguf | GGUF | Q3_K_S | 8.78 GB | Download |
| UNA-ThePitbull-21.4B-v2.i1-Q4_0.gguf | GGUF | — | 11.40 GB | Download |
| UNA-ThePitbull-21.4B-v2.i1-Q4_K_M.gguf | GGUF | Q4_K_M | 12.03 GB | Download |
| UNA-ThePitbull-21.4B-v2.i1-Q4_K_S.gguf | GGUF | Q4_K_S | 11.44 GB | Download |
| UNA-ThePitbull-21.4B-v2.i1-Q5_K_M.gguf | GGUF | Q5_K_M | 14.13 GB | Download |
| UNA-ThePitbull-21.4B-v2.i1-Q5_K_S.gguf | GGUF | Q5_K_S | 13.79 GB | Download |
| UNA-ThePitbull-21.4B-v2.i1-Q6_K.gguf | GGUF | Q6_K | 16.37 GB | Download |
Model Details Live
Metadata Inspector
Normalized metadata (stored in metadata_json)
{
"metadata": {},
"card_data": {
"base_model": "fblgit/UNA-ThePitbull-21.4B-v2",
"datasets": [
"jondurbin/py-dpo-v0.1",
"Replete-AI/code_bagel_hermes-2.5",
"mlabonne/orpo-dpo-mix-40k"
],
"language": [
"en"
],
"library_name": "transformers",
"license": "afl-3.0",
"quantized_by": "mradermacher",
"tags": [
"UNA",
"juanako"
],
"frontmatter": {
"base_model": "fblgit/UNA-ThePitbull-21.4B-v2",
"datasets": [
"jondurbin/py-dpo-v0.1",
"Replete-AI/code_bagel_hermes-2.5",
"mlabonne/orpo-dpo-mix-40k"
],
"language": [
"en"
],
"library_name": "transformers",
"license": "afl-3.0",
"quantized_by": "mradermacher",
"tags": [
"UNA",
"juanako"
]
},
"hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
"summary": "## About weighted/imatrix quants of https://huggingface.co/fblgit/UNA-ThePitbull-21.4B-v2 static quants are available at https://huggingface.co/mradermacher/UNA-ThePitbull-21.4B-v2-GGUF",
"quick_links": [],
"benchmark_table_html": "",
"readme_markdown": "---\nbase_model: fblgit/UNA-ThePitbull-21.4B-v2\ndatasets:\n- jondurbin/py-dpo-v0.1\n- Replete-AI/code_bagel_hermes-2.5\n- mlabonne/orpo-dpo-mix-40k\nlanguage:\n- en\nlibrary_name: transformers\nlicense: afl-3.0\nquantized_by: mradermacher\ntags:\n- UNA\n- juanako\n---\n## About\n\n<!-- ### quantize_version: 2 -->\n<!-- ### output_tensor_quantised: 1 -->\n<!-- ### convert_type: hf -->\n<!-- ### vocab_type: -->\n<!-- ### tags: nicoboss -->\nweighted/imatrix quants of https://huggingface.co/fblgit/UNA-ThePitbull-21.4B-v2\n\n<!-- provided-files -->\nstatic quants are available at https://huggingface.co/mradermacher/UNA-ThePitbull-21.4B-v2-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/UNA-ThePitbull-21.4B-v2-i1-GGUF/resolve/main/UNA-ThePitbull-21.4B-v2.i1-IQ1_S.gguf) | i1-IQ1_S | 5.0 | for the desperate |\n| [GGUF](https://huggingface.co/mradermacher/UNA-ThePitbull-21.4B-v2-i1-GGUF/resolve/main/UNA-ThePitbull-21.4B-v2.i1-IQ1_M.gguf) | i1-IQ1_M | 5.4 | mostly desperate |\n| [GGUF](https://huggingface.co/mradermacher/UNA-ThePitbull-21.4B-v2-i1-GGUF/resolve/main/UNA-ThePitbull-21.4B-v2.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 6.1 | |\n| [GGUF](https://huggingface.co/mradermacher/UNA-ThePitbull-21.4B-v2-i1-GGUF/resolve/main/UNA-ThePitbull-21.4B-v2.i1-IQ2_XS.gguf) | i1-IQ2_XS | 6.7 | |\n| [GGUF](https://huggingface.co/mradermacher/UNA-ThePitbull-21.4B-v2-i1-GGUF/resolve/main/UNA-ThePitbull-21.4B-v2.i1-IQ2_S.gguf) | i1-IQ2_S | 7.1 | |\n| [GGUF](https://huggingface.co/mradermacher/UNA-ThePitbull-21.4B-v2-i1-GGUF/resolve/main/UNA-ThePitbull-21.4B-v2.i1-IQ2_M.gguf) | i1-IQ2_M | 7.6 | |\n| [GGUF](https://huggingface.co/mradermacher/UNA-ThePitbull-21.4B-v2-i1-GGUF/resolve/main/UNA-ThePitbull-21.4B-v2.i1-Q2_K.gguf) | i1-Q2_K | 8.2 | IQ3_XXS probably better |\n| [GGUF](https://huggingface.co/mradermacher/UNA-ThePitbull-21.4B-v2-i1-GGUF/resolve/main/UNA-ThePitbull-21.4B-v2.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 8.5 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/UNA-ThePitbull-21.4B-v2-i1-GGUF/resolve/main/UNA-ThePitbull-21.4B-v2.i1-IQ3_XS.gguf) | i1-IQ3_XS | 9.1 | |\n| [GGUF](https://huggingface.co/mradermacher/UNA-ThePitbull-21.4B-v2-i1-GGUF/resolve/main/UNA-ThePitbull-21.4B-v2.i1-Q3_K_S.gguf) | i1-Q3_K_S | 9.5 | IQ3_XS probably better |\n| [GGUF](https://huggingface.co/mradermacher/UNA-ThePitbull-21.4B-v2-i1-GGUF/resolve/main/UNA-ThePitbull-21.4B-v2.i1-IQ3_S.gguf) | i1-IQ3_S | 9.6 | beats Q3_K* |\n| [GGUF](https://huggingface.co/mradermacher/UNA-ThePitbull-21.4B-v2-i1-GGUF/resolve/main/UNA-ThePitbull-21.4B-v2.i1-IQ3_M.gguf) | i1-IQ3_M | 9.9 | |\n| [GGUF](https://huggingface.co/mradermacher/UNA-ThePitbull-21.4B-v2-i1-GGUF/resolve/main/UNA-ThePitbull-21.4B-v2.i1-Q3_K_M.gguf) | i1-Q3_K_M | 10.6 | IQ3_S probably better |\n| [GGUF](https://huggingface.co/mradermacher/UNA-ThePitbull-21.4B-v2-i1-GGUF/resolve/main/UNA-ThePitbull-21.4B-v2.i1-Q3_K_L.gguf) | i1-Q3_K_L | 11.5 | IQ3_M probably better |\n| [GGUF](https://huggingface.co/mradermacher/UNA-ThePitbull-21.4B-v2-i1-GGUF/resolve/main/UNA-ThePitbull-21.4B-v2.i1-IQ4_XS.gguf) | i1-IQ4_XS | 11.7 | |\n| [GGUF](https://huggingface.co/mradermacher/UNA-ThePitbull-21.4B-v2-i1-GGUF/resolve/main/UNA-ThePitbull-21.4B-v2.i1-Q4_0.gguf) | i1-Q4_0 | 12.3 | fast, low quality |\n| [GGUF](https://huggingface.co/mradermacher/UNA-ThePitbull-21.4B-v2-i1-GGUF/resolve/main/UNA-ThePitbull-21.4B-v2.i1-Q4_K_S.gguf) | i1-Q4_K_S | 12.4 | optimal size/speed/quality |\n| [GGUF](https://huggingface.co/mradermacher/UNA-ThePitbull-21.4B-v2-i1-GGUF/resolve/main/UNA-ThePitbull-21.4B-v2.i1-Q4_K_M.gguf) | i1-Q4_K_M | 13.0 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/UNA-ThePitbull-21.4B-v2-i1-GGUF/resolve/main/UNA-ThePitbull-21.4B-v2.i1-Q5_K_S.gguf) | i1-Q5_K_S | 14.9 | |\n| [GGUF](https://huggingface.co/mradermacher/UNA-ThePitbull-21.4B-v2-i1-GGUF/resolve/main/UNA-ThePitbull-21.4B-v2.i1-Q5_K_M.gguf) | i1-Q5_K_M | 15.3 | |\n| [GGUF](https://huggingface.co/mradermacher/UNA-ThePitbull-21.4B-v2-i1-GGUF/resolve/main/UNA-ThePitbull-21.4B-v2.i1-Q6_K.gguf) | i1-Q6_K | 17.7 | 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": [
"transformers",
"gguf",
"UNA",
"juanako",
"en",
"dataset:jondurbin/py-dpo-v0.1",
"dataset:Replete-AI/code_bagel_hermes-2.5",
"dataset:mlabonne/orpo-dpo-mix-40k",
"base_model:fblgit/UNA-ThePitbull-21.4B-v2",
"base_model:quantized:fblgit/UNA-ThePitbull-21.4B-v2",
"license:afl-3.0",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
],
"likes": 0,
"downloads": 177,
"gated": false,
"private": false,
"last_modified": "2024-11-13T01:02:10.000Z",
"created_at": "2024-11-12T21:15:09.000Z",
"pipeline_tag": "",
"library_name": "transformers"
}
Source payload excerpt (from Hugging Face API)
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"sha": "9bc94656cf3621bf720cc89ba311dcc268024581",
"createdAt": "2024-11-12T21:15:09.000Z",
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