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Radiantloom/distilabel-intel-orca-dpo-pairs-chatml

published by @Radiantloom

Alignment dataset tracked in the /datasets sub-catalog.

Lifetime downloads
566
Last 30 days
26
Likes
-
Size
18.7 MB
Created on HF
2024-02-20
Age
2 years ago

Tags

license:apache-2.0size_categories:10K<n<100Kformat:parquetmodality:textlibrary:datasetslibrary:pandaslibrary:mlcroissantlibrary:polarsregion:us

README current version from Hugging Face


dataset_info:
features:

  • name: chosen
    dtype: string
  • name: rejected
    dtype: string
  • name: prompt
    dtype: string
    splits:
  • name: train
    num_bytes: 36184827
    num_examples: 12859
    download_size: 19625730
    dataset_size: 36184827
    configs:
  • config_name: default
    data_files:
    • split: train
      path: data/train-*
      license: apache-2.0

README history 3 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. 2024-02-20Update README.md58d706f371 B
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  2. 2024-02-20Upload datasetf0098a6352 B
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  3. 2024-02-20initial commit90593300 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. 2024-07-01PRLibrarian Bot: Add dpo tagopen1 💬#2
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  2. 2024-02-21[bot] Conversion to Parquetopen1 💬#1
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Metadata

License
apache-2.0

Repository

Download the dataset

0

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("Radiantloom/distilabel-intel-orca-dpo-pairs-chatml")
Raw snapshot (Python)
from huggingface_hub import snapshot_download
snapshot_download(repo_id="Radiantloom/distilabel-intel-orca-dpo-pairs-chatml", repo_type="dataset")
git clone (requires git-lfs)
git clone https://huggingface.co/datasets/Radiantloom/distilabel-intel-orca-dpo-pairs-chatml
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