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llmat/dpo-orpo-mix-45k

published by @llmat

Alignment dataset tracked in the /datasets sub-catalog.

Lifetime downloads
687
Last 30 days
37
Likes
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Size
111.3 MB
Created on HF
2024-08-01
Age
2 years ago

Description

DPO-ORPO-mix-45k

This dataset is designed for DPO or ORPO training.

This dataset combines samples of the following high-quality DPO datasets:

argilla/Capybara-Preferences: highly scored chosen answers >=5 (2882 samples)

argilla/distilabel-intel-orca-dpo-pairs: highly scored chosen answers >=9, not in GSM8K (3961 samples)

argilla/ultrafeedback-binarized-preferences-cleaned: highly scored chosen answers >=5 (22799 samples)

argilla/distilabel-math-preference-dpo: highly scored… See the full description on the dataset page: https://huggingface.co/datasets/llmat/dpo-orpo-mix-45k.

Tags

task_categories:text-generationlanguage:enlicense:apache-2.0size_categories:10K<n<100Kformat:parquetmodality:textlibrary:datasetslibrary:pandaslibrary:mlcroissantlibrary:polarsregion:usdpopreferenceorpo

README current version from Hugging Face

dataset_info:
features:

  • name: origin
    dtype: string
  • name: chosen
    list:
    • name: content
      dtype: string
    • name: role
      dtype: string
  • name: rejected
    list:
    • name: content
      dtype: string
    • name: role
      dtype: string
  • name: prompt
    dtype: string
    splits:
  • name: train
    num_bytes: 221413560
    num_examples: 45011
    download_size: 116720118
    dataset_size: 221413560
    configs:
  • config_name: default
    data_files:
    • split: train
      path: data/train-*
      license: apache-2.0
      task_categories:
  • text-generation
    language:
  • en
    size_categories:
  • 10K<n<100K
    tags:
  • dpo
  • preference
  • orpo

DPO-ORPO-mix-45k

This dataset is designed for DPO or ORPO training.
This dataset combines samples of the following high-quality DPO datasets:

Thanks to argilla, unalignment, M4-ai, and jondurbin for providing the source datasets.

README history 5 revisions

Every night we snapshot the README of every dataset in the catalog. When the SHA changes we archive the new version and diff it against the last. This is the evolving thought record of the alignment-data field: what the author decided to say about the corpus, and how that framing shifted over time.

  1. 2024-08-03Update README.md64513842.2 KB
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  2. 2024-08-03Update README.md5ddf8fa2.2 KB
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  3. 2024-08-03Update README.mde3ef09d2.2 KB
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  4. 2024-08-01Upload datasetb8156ea528 B
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  5. 2024-08-01initial commitf1f213b0 B
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Used by abliterated models none yet

No abliterated models in our catalog have declared this dataset in their YAML metadata yet. This can mean the dataset is used but not declared, is used outside abliteration workflows, or is new. The link will populate automatically as models are indexed.

Community discussions 2 threads · 2 open · 2 comments

Threads posted by the community on Hugging Face: bug reports, questions about usage, pull requests on the README, license clarifications. Click any thread to expand and read the full conversation inline. Newest first.

  1. 2024-08-03PRLibrarian Bot: Add language metadata for datasetopen1 💬#2
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  2. 2024-08-02[bot] Conversion to Parquetopen1 💬#1
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Read further

Community best practices (healing)
4 rules on DPO/ORPO, GSM8K lag, CHES filtering, and what heal does not do.
M4 - Abliterate then heal
Two-stage pipeline. DPO healing recovers benchmarks.
The politics of dataset curation
Whose preferences are baked into the healing mix, and why it matters.
Non-English abliteration communities
The Russian slop-removal framing and non-English healing corpora.

Metadata

License
apache-2.0

Repository

DIR data FILE .gitattributes FILE README.md

File contents live on Hugging Face. Click a file or folder to open it there.

Download the dataset

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Copy any of these snippets into your notebook or terminal. All three fetch directly from Hugging Face using your own credentials.

Recommended: datasets library (Python) 
from datasets import load_dataset
ds = load_dataset("llmat/dpo-orpo-mix-45k")
Raw snapshot (Python) 
from huggingface_hub import snapshot_download
snapshot_download(repo_id="llmat/dpo-orpo-mix-45k", repo_type="dataset")
git clone (requires git-lfs) 
git clone https://huggingface.co/datasets/llmat/dpo-orpo-mix-45k
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