mradermacher/bagel-dpo-20b-v04-i1-gguf IQ2_S 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.
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mradermacher/bagel-dpo-20b-v04-i1-gguf overview
About weighted/imatrix quants of https://huggingface.co/jondurbin/bagel-dpo-20b-v04 This uses only 95k tokens of my standard set, as the model overflowed with more. static quants are available at https://huggingface.co/mradermacher/bagel-dpo-20b-v04-GGUF
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Repository Files & Downloads
21 files detected
Direct downloads for all repository files
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| bagel-dpo-20b-v04.i1-IQ1_M.gguf | GGUF | IQ1_M | 5.28 GB | Download |
| bagel-dpo-20b-v04.i1-IQ1_S.gguf | GGUF | IQ1_S | 4.93 GB | Download |
| bagel-dpo-20b-v04.i1-IQ2_M.gguf | GGUF | IQ2_M | 7.19 GB | Download |
| bagel-dpo-20b-v04.i1-IQ2_S.gguf | GGUF | IQ2_S | 6.72 GB | Download |
| bagel-dpo-20b-v04.i1-IQ2_XS.gguf | GGUF | IQ2_XS | 6.38 GB | Download |
| bagel-dpo-20b-v04.i1-IQ2_XXS.gguf | GGUF | IQ2_XXS | 5.86 GB | Download |
| bagel-dpo-20b-v04.i1-IQ3_M.gguf | GGUF | IQ3_M | 9.12 GB | Download |
| bagel-dpo-20b-v04.i1-IQ3_S.gguf | GGUF | IQ3_S | 8.82 GB | Download |
| bagel-dpo-20b-v04.i1-IQ3_XS.gguf | GGUF | IQ3_XS | 8.41 GB | Download |
| bagel-dpo-20b-v04.i1-IQ3_XXS.gguf | GGUF | IQ3_XXS | 7.97 GB | Download |
| bagel-dpo-20b-v04.i1-IQ4_XS.gguf | GGUF | IQ4_XS | 10.65 GB | Download |
| bagel-dpo-20b-v04.i1-Q2_K.gguf | GGUF | Q2_K | 7.65 GB | Download |
| bagel-dpo-20b-v04.i1-Q3_K_L.gguf | GGUF | Q3_K_L | 10.45 GB | Download |
| bagel-dpo-20b-v04.i1-Q3_K_M.gguf | GGUF | Q3_K_M | 9.68 GB | Download |
| bagel-dpo-20b-v04.i1-Q3_K_S.gguf | GGUF | Q3_K_S | 8.78 GB | Download |
| bagel-dpo-20b-v04.i1-Q4_0.gguf | GGUF | — | 11.20 GB | Download |
| bagel-dpo-20b-v04.i1-Q4_K_M.gguf | GGUF | Q4_K_M | 11.79 GB | Download |
| bagel-dpo-20b-v04.i1-Q4_K_S.gguf | GGUF | Q4_K_S | 11.24 GB | Download |
| bagel-dpo-20b-v04.i1-Q5_K_M.gguf | GGUF | Q5_K_M | 13.73 GB | Download |
| bagel-dpo-20b-v04.i1-Q5_K_S.gguf | GGUF | Q5_K_S | 13.42 GB | Download |
| bagel-dpo-20b-v04.i1-Q6_K.gguf | GGUF | Q6_K | 15.80 GB | Download |
Model Details Live
Metadata Inspector
Normalized metadata (stored in metadata_json)
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"metadata": {},
"card_data": {
"base_model": "jondurbin/bagel-dpo-20b-v04",
"datasets": [
"ai2_arc",
"allenai/ultrafeedback_binarized_cleaned",
"argilla/distilabel-intel-orca-dpo-pairs",
"jondurbin/airoboros-3.2",
"codeparrot/apps",
"facebook/belebele",
"bluemoon-fandom-1-1-rp-cleaned",
"boolq",
"camel-ai/biology",
"camel-ai/chemistry",
"camel-ai/math",
"camel-ai/physics",
"jondurbin/contextual-dpo-v0.1",
"jondurbin/gutenberg-dpo-v0.1",
"jondurbin/py-dpo-v0.1",
"jondurbin/truthy-dpo-v0.1",
"LDJnr/Capybara",
"jondurbin/cinematika-v0.1",
"WizardLM/WizardLM_evol_instruct_70k",
"glaiveai/glaive-function-calling-v2",
"jondurbin/gutenberg-dpo-v0.1",
"grimulkan/LimaRP-augmented",
"lmsys/lmsys-chat-1m",
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"Vezora/Tested-22k-Python-Alpaca",
"ropes",
"cakiki/rosetta-code",
"Open-Orca/SlimOrca",
"b-mc2/sql-create-context",
"squad_v2",
"mattpscott/airoboros-summarization",
"migtissera/Synthia-v1.3",
"unalignment/toxic-dpo-v0.2",
"WhiteRabbitNeo/WRN-Chapter-1",
"WhiteRabbitNeo/WRN-Chapter-2",
"winogrande"
],
"language": [
"en"
],
"library_name": "transformers",
"license": "other",
"license_link": "https://huggingface.co/internlm/internlm2-20b#open-source-license",
"license_name": "internlm2-20b",
"quantized_by": "mradermacher",
"frontmatter": {
"base_model": "jondurbin/bagel-dpo-20b-v04",
"datasets": [
"ai2_arc",
"allenai/ultrafeedback_binarized_cleaned",
"argilla/distilabel-intel-orca-dpo-pairs",
"jondurbin/airoboros-3.2",
"codeparrot/apps",
"facebook/belebele",
"bluemoon-fandom-1-1-rp-cleaned",
"boolq",
"camel-ai/biology",
"camel-ai/chemistry",
"camel-ai/math",
"camel-ai/physics",
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"LDJnr/Capybara",
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"summary": "## About weighted/imatrix quants of https://huggingface.co/jondurbin/bagel-dpo-20b-v04 **This uses only 95k tokens of my standard set, as the model overflowed with more.** static quants are available at https://huggingface.co/mradermacher/bagel-dpo-20b-v04-GGUF",
"quick_links": [],
"benchmark_table_html": "",
"readme_markdown": "---\nbase_model: jondurbin/bagel-dpo-20b-v04\ndatasets:\n- ai2_arc\n- allenai/ultrafeedback_binarized_cleaned\n- argilla/distilabel-intel-orca-dpo-pairs\n- jondurbin/airoboros-3.2\n- codeparrot/apps\n- facebook/belebele\n- bluemoon-fandom-1-1-rp-cleaned\n- boolq\n- camel-ai/biology\n- camel-ai/chemistry\n- camel-ai/math\n- camel-ai/physics\n- jondurbin/contextual-dpo-v0.1\n- jondurbin/gutenberg-dpo-v0.1\n- jondurbin/py-dpo-v0.1\n- jondurbin/truthy-dpo-v0.1\n- LDJnr/Capybara\n- jondurbin/cinematika-v0.1\n- WizardLM/WizardLM_evol_instruct_70k\n- glaiveai/glaive-function-calling-v2\n- jondurbin/gutenberg-dpo-v0.1\n- grimulkan/LimaRP-augmented\n- lmsys/lmsys-chat-1m\n- ParisNeo/lollms_aware_dataset\n- TIGER-Lab/MathInstruct\n- Muennighoff/natural-instructions\n- openbookqa\n- kingbri/PIPPA-shareGPT\n- piqa\n- Vezora/Tested-22k-Python-Alpaca\n- ropes\n- cakiki/rosetta-code\n- Open-Orca/SlimOrca\n- b-mc2/sql-create-context\n- squad_v2\n- mattpscott/airoboros-summarization\n- migtissera/Synthia-v1.3\n- unalignment/toxic-dpo-v0.2\n- WhiteRabbitNeo/WRN-Chapter-1\n- WhiteRabbitNeo/WRN-Chapter-2\n- winogrande\nlanguage:\n- en\nlibrary_name: transformers\nlicense: other\nlicense_link: https://huggingface.co/internlm/internlm2-20b#open-source-license\nlicense_name: internlm2-20b\nquantized_by: mradermacher\n---\n## About\n\n<!-- ### convert_type: -->\n<!-- ### vocab_type: -->\nweighted/imatrix quants of https://huggingface.co/jondurbin/bagel-dpo-20b-v04\n\n**This uses only 95k tokens of my standard set, as the model overflowed with more.**\n\n<!-- provided-files -->\nstatic quants are available at https://huggingface.co/mradermacher/bagel-dpo-20b-v04-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/bagel-dpo-20b-v04-i1-GGUF/resolve/main/bagel-dpo-20b-v04.i1-IQ1_S.gguf) | i1-IQ1_S | 5.4 | for the desperate |\n| [GGUF](https://huggingface.co/mradermacher/bagel-dpo-20b-v04-i1-GGUF/resolve/main/bagel-dpo-20b-v04.i1-IQ1_M.gguf) | i1-IQ1_M | 5.8 | mostly desperate |\n| [GGUF](https://huggingface.co/mradermacher/bagel-dpo-20b-v04-i1-GGUF/resolve/main/bagel-dpo-20b-v04.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 6.4 | |\n| [GGUF](https://huggingface.co/mradermacher/bagel-dpo-20b-v04-i1-GGUF/resolve/main/bagel-dpo-20b-v04.i1-IQ2_XS.gguf) | i1-IQ2_XS | 6.9 | |\n| [GGUF](https://huggingface.co/mradermacher/bagel-dpo-20b-v04-i1-GGUF/resolve/main/bagel-dpo-20b-v04.i1-IQ2_S.gguf) | i1-IQ2_S | 7.3 | |\n| [GGUF](https://huggingface.co/mradermacher/bagel-dpo-20b-v04-i1-GGUF/resolve/main/bagel-dpo-20b-v04.i1-IQ2_M.gguf) | i1-IQ2_M | 7.8 | |\n| [GGUF](https://huggingface.co/mradermacher/bagel-dpo-20b-v04-i1-GGUF/resolve/main/bagel-dpo-20b-v04.i1-Q2_K.gguf) | i1-Q2_K | 8.3 | IQ3_XXS probably better |\n| [GGUF](https://huggingface.co/mradermacher/bagel-dpo-20b-v04-i1-GGUF/resolve/main/bagel-dpo-20b-v04.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 8.7 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/bagel-dpo-20b-v04-i1-GGUF/resolve/main/bagel-dpo-20b-v04.i1-IQ3_XS.gguf) | i1-IQ3_XS | 9.1 | |\n| [GGUF](https://huggingface.co/mradermacher/bagel-dpo-20b-v04-i1-GGUF/resolve/main/bagel-dpo-20b-v04.i1-Q3_K_S.gguf) | i1-Q3_K_S | 9.5 | IQ3_XS probably better |\n| [GGUF](https://huggingface.co/mradermacher/bagel-dpo-20b-v04-i1-GGUF/resolve/main/bagel-dpo-20b-v04.i1-IQ3_S.gguf) | i1-IQ3_S | 9.6 | beats Q3_K* |\n| [GGUF](https://huggingface.co/mradermacher/bagel-dpo-20b-v04-i1-GGUF/resolve/main/bagel-dpo-20b-v04.i1-IQ3_M.gguf) | i1-IQ3_M | 9.9 | |\n| [GGUF](https://huggingface.co/mradermacher/bagel-dpo-20b-v04-i1-GGUF/resolve/main/bagel-dpo-20b-v04.i1-Q3_K_M.gguf) | i1-Q3_K_M | 10.5 | IQ3_S probably better |\n| [GGUF](https://huggingface.co/mradermacher/bagel-dpo-20b-v04-i1-GGUF/resolve/main/bagel-dpo-20b-v04.i1-Q3_K_L.gguf) | i1-Q3_K_L | 11.3 | IQ3_M probably better |\n| [GGUF](https://huggingface.co/mradermacher/bagel-dpo-20b-v04-i1-GGUF/resolve/main/bagel-dpo-20b-v04.i1-IQ4_XS.gguf) | i1-IQ4_XS | 11.5 | |\n| [GGUF](https://huggingface.co/mradermacher/bagel-dpo-20b-v04-i1-GGUF/resolve/main/bagel-dpo-20b-v04.i1-Q4_0.gguf) | i1-Q4_0 | 12.1 | fast, low quality |\n| [GGUF](https://huggingface.co/mradermacher/bagel-dpo-20b-v04-i1-GGUF/resolve/main/bagel-dpo-20b-v04.i1-Q4_K_S.gguf) | i1-Q4_K_S | 12.2 | optimal size/speed/quality |\n| [GGUF](https://huggingface.co/mradermacher/bagel-dpo-20b-v04-i1-GGUF/resolve/main/bagel-dpo-20b-v04.i1-Q4_K_M.gguf) | i1-Q4_K_M | 12.8 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/bagel-dpo-20b-v04-i1-GGUF/resolve/main/bagel-dpo-20b-v04.i1-Q5_K_S.gguf) | i1-Q5_K_S | 14.5 | |\n| [GGUF](https://huggingface.co/mradermacher/bagel-dpo-20b-v04-i1-GGUF/resolve/main/bagel-dpo-20b-v04.i1-Q5_K_M.gguf) | i1-Q5_K_M | 14.8 | |\n| [GGUF](https://huggingface.co/mradermacher/bagel-dpo-20b-v04-i1-GGUF/resolve/main/bagel-dpo-20b-v04.i1-Q6_K.gguf) | i1-Q6_K | 17.1 | 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.\n\n<!-- end -->\n",
"related_quantizations": []
},
"tags": [
"transformers",
"gguf",
"en",
"dataset:ai2_arc",
"dataset:allenai/ultrafeedback_binarized_cleaned",
"dataset:argilla/distilabel-intel-orca-dpo-pairs",
"dataset:jondurbin/airoboros-3.2",
"dataset:codeparrot/apps",
"dataset:facebook/belebele",
"dataset:bluemoon-fandom-1-1-rp-cleaned",
"dataset:boolq",
"dataset:camel-ai/biology",
"dataset:camel-ai/chemistry",
"dataset:camel-ai/math",
"dataset:camel-ai/physics",
"dataset:jondurbin/contextual-dpo-v0.1",
"dataset:jondurbin/gutenberg-dpo-v0.1",
"dataset:jondurbin/py-dpo-v0.1",
"dataset:jondurbin/truthy-dpo-v0.1",
"dataset:LDJnr/Capybara",
"dataset:jondurbin/cinematika-v0.1",
"dataset:WizardLM/WizardLM_evol_instruct_70k",
"dataset:glaiveai/glaive-function-calling-v2",
"dataset:grimulkan/LimaRP-augmented",
"dataset:lmsys/lmsys-chat-1m",
"dataset:ParisNeo/lollms_aware_dataset",
"dataset:TIGER-Lab/MathInstruct",
"dataset:Muennighoff/natural-instructions",
"dataset:openbookqa",
"dataset:kingbri/PIPPA-shareGPT",
"dataset:piqa",
"dataset:Vezora/Tested-22k-Python-Alpaca",
"dataset:ropes",
"dataset:cakiki/rosetta-code",
"dataset:Open-Orca/SlimOrca",
"dataset:b-mc2/sql-create-context",
"dataset:squad_v2",
"dataset:mattpscott/airoboros-summarization",
"dataset:migtissera/Synthia-v1.3",
"dataset:unalignment/toxic-dpo-v0.2",
"dataset:WhiteRabbitNeo/WRN-Chapter-1",
"dataset:WhiteRabbitNeo/WRN-Chapter-2",
"dataset:winogrande",
"base_model:jondurbin/bagel-dpo-20b-v04",
"base_model:quantized:jondurbin/bagel-dpo-20b-v04",
"license:other",
"endpoints_compatible",
"region:us",
"conversational"
],
"likes": 1,
"downloads": 323,
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"last_modified": "2024-05-06T05:21:57.000Z",
"created_at": "2024-04-02T23:46:09.000Z",
"pipeline_tag": "",
"library_name": "transformers"
}
Source payload excerpt (from Hugging Face API)
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