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mradermacher/ultrafeedback-binarized-tulu-2-7b-dpo-full-i1-gguf overview

About weighted/imatrix quants of https://huggingface.co/NicholasCorrado/ultrafeedback-binarized-tulu-2-7b-dpo-full static quants are available at https://huggingface.co/mradermacher/ultrafeedback-binarized-tulu-2-7b-dpo-full-GGUF

transformersggufalignment-handbooktrldpogenerated_from_trainerendataset:HuggingFaceH4/ultrafeedback_binarizedbase_model:NicholasCorrado/ultrafeedback-binarized-tulu-2-7b-dpo-fullbase_model:quantized:NicholasCorrado/ultrafeedback-binarized-tulu-2-7b-dpo-fullendpoints_compatibleregion:usimatrixconversational
mradermacher/ultrafeedback-binarized-tulu-2-7b-dpo-full-i1-gguf visual
Downloads
112
Likes
0
Pipeline
Library
transformers
Visibility
Public
Access
Open

Repository Files & Downloads

21 files detected
Direct downloads for all repository files
FileTypeQuantizationSizeLink
ultrafeedback-binarized-tulu-2-7b-dpo-full.i1-IQ1_M.gguf GGUF IQ1_M 1.54 GB Download
ultrafeedback-binarized-tulu-2-7b-dpo-full.i1-IQ1_S.gguf GGUF IQ1_S 1.42 GB Download
ultrafeedback-binarized-tulu-2-7b-dpo-full.i1-IQ2_M.gguf GGUF IQ2_M 2.20 GB Download
ultrafeedback-binarized-tulu-2-7b-dpo-full.i1-IQ2_S.gguf GGUF IQ2_S 2.05 GB Download
ultrafeedback-binarized-tulu-2-7b-dpo-full.i1-IQ2_XS.gguf GGUF IQ2_XS 1.90 GB Download
ultrafeedback-binarized-tulu-2-7b-dpo-full.i1-IQ2_XXS.gguf GGUF IQ2_XXS 1.73 GB Download
ultrafeedback-binarized-tulu-2-7b-dpo-full.i1-IQ3_M.gguf GGUF IQ3_M 2.90 GB Download
ultrafeedback-binarized-tulu-2-7b-dpo-full.i1-IQ3_S.gguf GGUF IQ3_S 2.75 GB Download
ultrafeedback-binarized-tulu-2-7b-dpo-full.i1-IQ3_XS.gguf GGUF IQ3_XS 2.60 GB Download
ultrafeedback-binarized-tulu-2-7b-dpo-full.i1-IQ3_XXS.gguf GGUF IQ3_XXS 2.41 GB Download
ultrafeedback-binarized-tulu-2-7b-dpo-full.i1-IQ4_XS.gguf GGUF IQ4_XS 3.37 GB Download
ultrafeedback-binarized-tulu-2-7b-dpo-full.i1-Q2_K.gguf GGUF Q2_K 2.36 GB Download
ultrafeedback-binarized-tulu-2-7b-dpo-full.i1-Q3_K_L.gguf GGUF Q3_K_L 3.35 GB Download
ultrafeedback-binarized-tulu-2-7b-dpo-full.i1-Q3_K_M.gguf GGUF Q3_K_M 3.07 GB Download
ultrafeedback-binarized-tulu-2-7b-dpo-full.i1-Q3_K_S.gguf GGUF Q3_K_S 2.75 GB Download
ultrafeedback-binarized-tulu-2-7b-dpo-full.i1-Q4_0.gguf GGUF 3.57 GB Download
ultrafeedback-binarized-tulu-2-7b-dpo-full.i1-Q4_K_M.gguf GGUF Q4_K_M 3.80 GB Download
ultrafeedback-binarized-tulu-2-7b-dpo-full.i1-Q4_K_S.gguf GGUF Q4_K_S 3.59 GB Download
ultrafeedback-binarized-tulu-2-7b-dpo-full.i1-Q5_K_M.gguf GGUF Q5_K_M 4.45 GB Download
ultrafeedback-binarized-tulu-2-7b-dpo-full.i1-Q5_K_S.gguf GGUF Q5_K_S 4.33 GB Download
ultrafeedback-binarized-tulu-2-7b-dpo-full.i1-Q6_K.gguf GGUF Q6_K 5.15 GB Download

Model Details Live

Model Slug
mradermacher/ultrafeedback-binarized-tulu-2-7b-dpo-full-i1-gguf
Author
mradermacher
Pipeline Task
Library
transformers
Created
2024-08-29
Last Modified
2024-08-29
Gated
No
Private
No
HF SHA
5a0283325da9e0f52cb0a18445947371a77236af
License
Unknown
Language
en
Base Model
NicholasCorrado/ultrafeedback-binarized-tulu-2-7b-dpo-full

Metadata Inspector

Normalized metadata (stored in metadata_json)
{
  "metadata": {},
  "card_data": {
    "base_model": "NicholasCorrado/ultrafeedback-binarized-tulu-2-7b-dpo-full",
    "datasets": [
      "HuggingFaceH4/ultrafeedback_binarized"
    ],
    "language": [
      "en"
    ],
    "library_name": "transformers",
    "quantized_by": "mradermacher",
    "tags": [
      "alignment-handbook",
      "trl",
      "dpo",
      "generated_from_trainer",
      "trl",
      "dpo",
      "generated_from_trainer"
    ],
    "frontmatter": {
      "base_model": "NicholasCorrado/ultrafeedback-binarized-tulu-2-7b-dpo-full",
      "datasets": [
        "HuggingFaceH4/ultrafeedback_binarized"
      ],
      "language": [
        "en"
      ],
      "library_name": "transformers",
      "quantized_by": "mradermacher",
      "tags": [
        "alignment-handbook",
        "trl",
        "dpo",
        "generated_from_trainer",
        "trl",
        "dpo",
        "generated_from_trainer"
      ]
    },
    "hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
    "summary": "## About      weighted/imatrix quants of https://huggingface.co/NicholasCorrado/ultrafeedback-binarized-tulu-2-7b-dpo-full  static quants are available at https://huggingface.co/mradermacher/ultrafeedback-binarized-tulu-2-7b-dpo-full-GGUF",
    "quick_links": [],
    "benchmark_table_html": "",
    "readme_markdown": "---\nbase_model: NicholasCorrado/ultrafeedback-binarized-tulu-2-7b-dpo-full\ndatasets:\n- HuggingFaceH4/ultrafeedback_binarized\nlanguage:\n- en\nlibrary_name: transformers\nquantized_by: mradermacher\ntags:\n- alignment-handbook\n- trl\n- dpo\n- generated_from_trainer\n- trl\n- dpo\n- generated_from_trainer\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/NicholasCorrado/ultrafeedback-binarized-tulu-2-7b-dpo-full\n\n<!-- provided-files -->\nstatic quants are available at https://huggingface.co/mradermacher/ultrafeedback-binarized-tulu-2-7b-dpo-full-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/ultrafeedback-binarized-tulu-2-7b-dpo-full-i1-GGUF/resolve/main/ultrafeedback-binarized-tulu-2-7b-dpo-full.i1-IQ1_S.gguf) | i1-IQ1_S | 1.6 | for the desperate |\n| [GGUF](https://huggingface.co/mradermacher/ultrafeedback-binarized-tulu-2-7b-dpo-full-i1-GGUF/resolve/main/ultrafeedback-binarized-tulu-2-7b-dpo-full.i1-IQ1_M.gguf) | i1-IQ1_M | 1.8 | mostly desperate |\n| [GGUF](https://huggingface.co/mradermacher/ultrafeedback-binarized-tulu-2-7b-dpo-full-i1-GGUF/resolve/main/ultrafeedback-binarized-tulu-2-7b-dpo-full.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 2.0 |  |\n| [GGUF](https://huggingface.co/mradermacher/ultrafeedback-binarized-tulu-2-7b-dpo-full-i1-GGUF/resolve/main/ultrafeedback-binarized-tulu-2-7b-dpo-full.i1-IQ2_XS.gguf) | i1-IQ2_XS | 2.1 |  |\n| [GGUF](https://huggingface.co/mradermacher/ultrafeedback-binarized-tulu-2-7b-dpo-full-i1-GGUF/resolve/main/ultrafeedback-binarized-tulu-2-7b-dpo-full.i1-IQ2_S.gguf) | i1-IQ2_S | 2.3 |  |\n| [GGUF](https://huggingface.co/mradermacher/ultrafeedback-binarized-tulu-2-7b-dpo-full-i1-GGUF/resolve/main/ultrafeedback-binarized-tulu-2-7b-dpo-full.i1-IQ2_M.gguf) | i1-IQ2_M | 2.5 |  |\n| [GGUF](https://huggingface.co/mradermacher/ultrafeedback-binarized-tulu-2-7b-dpo-full-i1-GGUF/resolve/main/ultrafeedback-binarized-tulu-2-7b-dpo-full.i1-Q2_K.gguf) | i1-Q2_K | 2.6 | IQ3_XXS probably better |\n| [GGUF](https://huggingface.co/mradermacher/ultrafeedback-binarized-tulu-2-7b-dpo-full-i1-GGUF/resolve/main/ultrafeedback-binarized-tulu-2-7b-dpo-full.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 2.7 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/ultrafeedback-binarized-tulu-2-7b-dpo-full-i1-GGUF/resolve/main/ultrafeedback-binarized-tulu-2-7b-dpo-full.i1-IQ3_XS.gguf) | i1-IQ3_XS | 2.9 |  |\n| [GGUF](https://huggingface.co/mradermacher/ultrafeedback-binarized-tulu-2-7b-dpo-full-i1-GGUF/resolve/main/ultrafeedback-binarized-tulu-2-7b-dpo-full.i1-IQ3_S.gguf) | i1-IQ3_S | 3.0 | beats Q3_K* |\n| [GGUF](https://huggingface.co/mradermacher/ultrafeedback-binarized-tulu-2-7b-dpo-full-i1-GGUF/resolve/main/ultrafeedback-binarized-tulu-2-7b-dpo-full.i1-Q3_K_S.gguf) | i1-Q3_K_S | 3.0 | IQ3_XS probably better |\n| [GGUF](https://huggingface.co/mradermacher/ultrafeedback-binarized-tulu-2-7b-dpo-full-i1-GGUF/resolve/main/ultrafeedback-binarized-tulu-2-7b-dpo-full.i1-IQ3_M.gguf) | i1-IQ3_M | 3.2 |  |\n| [GGUF](https://huggingface.co/mradermacher/ultrafeedback-binarized-tulu-2-7b-dpo-full-i1-GGUF/resolve/main/ultrafeedback-binarized-tulu-2-7b-dpo-full.i1-Q3_K_M.gguf) | i1-Q3_K_M | 3.4 | IQ3_S probably better |\n| [GGUF](https://huggingface.co/mradermacher/ultrafeedback-binarized-tulu-2-7b-dpo-full-i1-GGUF/resolve/main/ultrafeedback-binarized-tulu-2-7b-dpo-full.i1-Q3_K_L.gguf) | i1-Q3_K_L | 3.7 | IQ3_M probably better |\n| [GGUF](https://huggingface.co/mradermacher/ultrafeedback-binarized-tulu-2-7b-dpo-full-i1-GGUF/resolve/main/ultrafeedback-binarized-tulu-2-7b-dpo-full.i1-IQ4_XS.gguf) | i1-IQ4_XS | 3.7 |  |\n| [GGUF](https://huggingface.co/mradermacher/ultrafeedback-binarized-tulu-2-7b-dpo-full-i1-GGUF/resolve/main/ultrafeedback-binarized-tulu-2-7b-dpo-full.i1-Q4_0.gguf) | i1-Q4_0 | 3.9 | fast, low quality |\n| [GGUF](https://huggingface.co/mradermacher/ultrafeedback-binarized-tulu-2-7b-dpo-full-i1-GGUF/resolve/main/ultrafeedback-binarized-tulu-2-7b-dpo-full.i1-Q4_K_S.gguf) | i1-Q4_K_S | 4.0 | optimal size/speed/quality |\n| [GGUF](https://huggingface.co/mradermacher/ultrafeedback-binarized-tulu-2-7b-dpo-full-i1-GGUF/resolve/main/ultrafeedback-binarized-tulu-2-7b-dpo-full.i1-Q4_K_M.gguf) | i1-Q4_K_M | 4.2 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/ultrafeedback-binarized-tulu-2-7b-dpo-full-i1-GGUF/resolve/main/ultrafeedback-binarized-tulu-2-7b-dpo-full.i1-Q5_K_S.gguf) | i1-Q5_K_S | 4.8 |  |\n| [GGUF](https://huggingface.co/mradermacher/ultrafeedback-binarized-tulu-2-7b-dpo-full-i1-GGUF/resolve/main/ultrafeedback-binarized-tulu-2-7b-dpo-full.i1-Q5_K_M.gguf) | i1-Q5_K_M | 4.9 |  |\n| [GGUF](https://huggingface.co/mradermacher/ultrafeedback-binarized-tulu-2-7b-dpo-full-i1-GGUF/resolve/main/ultrafeedback-binarized-tulu-2-7b-dpo-full.i1-Q6_K.gguf) | i1-Q6_K | 5.6 | practically like static Q6_K |\n\nHere is a handy graph by ikawrakow comparing some lower-quality quant\ntypes (lower is better):\n\n![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png)\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",
    "alignment-handbook",
    "trl",
    "dpo",
    "generated_from_trainer",
    "en",
    "dataset:HuggingFaceH4/ultrafeedback_binarized",
    "base_model:NicholasCorrado/ultrafeedback-binarized-tulu-2-7b-dpo-full",
    "base_model:quantized:NicholasCorrado/ultrafeedback-binarized-tulu-2-7b-dpo-full",
    "endpoints_compatible",
    "region:us",
    "imatrix",
    "conversational"
  ],
  "likes": 0,
  "downloads": 112,
  "gated": false,
  "private": false,
  "last_modified": "2024-08-29T11:31:07.000Z",
  "created_at": "2024-08-29T09:31:37.000Z",
  "pipeline_tag": "",
  "library_name": "transformers"
}
Source payload excerpt (from Hugging Face API)
{
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  "sha": "5a0283325da9e0f52cb0a18445947371a77236af",
  "createdAt": "2024-08-29T09:31:37.000Z",
  "lastModified": "2024-08-29T11:31:07.000Z",
  "author": "mradermacher",
  "downloads": 112,
  "likes": 0,
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  "pipeline_tag": "",
  "library_name": "transformers",
  "siblings_count": 24
}