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catallama/Catalan-DPO-V2

published by @catallama

Alignment dataset tracked in the /datasets sub-catalog.

Lifetime downloads
713
Last 30 days
12
Likes
2
Size
47.1 MB
Created on HF
2024-07-13
Age
2 years ago

Description

Dataset Summary

The Catalan DPO V2 Dataset contains 23.5k sample preferences which is roughly 70% more than the Catalan DPO V1 dataset.

The dataset comprises of synthetically generated data and public preferences datasets:

argilla-orca: 9.5k preferences sampled from argilla/distilabel-intel-orca-dpo-pairs, out of which 50% were translated to Catalan

argilla-capybara: 7.2k preferences sampled from argilla/Capybara-Preferences-Filtered

6.8k preferences generated synthetically by… See the full description on the dataset page: https://huggingface.co/datasets/catallama/Catalan-DPO-V2.

Tags

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

README current version from Hugging Face

language:

  • en
  • ca
    dataset_info:
    features:
    • name: messages
      list:
      • name: content
        dtype: string
      • name: role
        dtype: string
    • name: chosen
      dtype: string
    • name: rejected
      dtype: string
      splits:
    • name: train
      num_bytes: 85381939
      num_examples: 23503
      download_size: 49394615
      dataset_size: 85381939
      configs:
  • config_name: default
    data_files:
    • split: train
      path: data/train-*
      license: apache-2.0
      task_categories:
  • text-generation
    tags:
  • catalan
    pretty_name: Catalan DPO V2
    size_categories:
  • 100K<n<1M

Dataset Summary

The Catalan DPO V2 Dataset contains 23.5k sample preferences which is roughly 70% more than the Catalan DPO V1 dataset.

The dataset comprises of synthetically generated data and public preferences datasets:

  • argilla-orca: 9.5k preferences sampled from argilla/distilabel-intel-orca-dpo-pairs, out of which 50% were translated to Catalan
  • argilla-capybara: 7.2k preferences sampled from argilla/Capybara-Preferences-Filtered
  • 6.8k preferences generated synthetically by inferencing catallama/CataLlama-v0.2-Instruct-SFT and scoring the results with RLHFlow/ArmoRM-Llama3-8B-v0.1

Languages

Catalan (ca-ES) - 40%

English (en-US) - 60%

Data Splits

The dataset contains one split: train.

README history 4 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. 2024-07-16Update README.md50170c71.4 KB
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  2. 2024-07-13Update README.md1769ab81.4 KB
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  3. 2024-07-13Upload dataset1b98786427 B
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  4. 2024-07-13initial commit68197080 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 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. 2024-07-14[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("catallama/Catalan-DPO-V2")
Raw snapshot (Python) 
from huggingface_hub import snapshot_download
snapshot_download(repo_id="catallama/Catalan-DPO-V2", repo_type="dataset")
git clone (requires git-lfs) 
git clone https://huggingface.co/datasets/catallama/Catalan-DPO-V2
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