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orangetin/orca-dpo-pairs-cleaned

published by @orangetin

Alignment dataset tracked in the /datasets sub-catalog.

Lifetime downloads
1.5K
Last 30 days
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Size
27.2 MB
Created on HF
2023-12-19
Age
2 years ago

Description

The dataset is a cleaned version of Intel/orca_dpo_pairs which is an Orca style dataset.

Notebook to reproduce result is in this repo.

Tags

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

README current version from Hugging Face

license: apache-2.0
language:

  • en

The dataset is a cleaned version of Intel/orca_dpo_pairs which is an Orca style dataset.

Notebook to reproduce result is in this repo.

README history 20 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.

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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 1 thread · 1 open · 1 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. 2023-12-21[bot] Conversion to Parquetopen1 💬#1
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Metadata

License
apache-2.0

Repository

DIR data 2 files FILE .gitattributes FILE format_intel_dpo_dataset.ipynb FILE README.md

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

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