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Finnish-NLP/distilabel-intel-orca-dpo-pairs-fi-deepl-translated-sft-dpo

published by @Finnish-NLP

Alignment dataset tracked in the /datasets sub-catalog.

Lifetime downloads
1.3K
Last 30 days
17
Likes
2
Size
40.4 MB
Created on HF
2024-02-07
Age
2 years ago

Description

README TO DO BUT RELEASED NEVERTHELESS

Tags

size_categories:1K<n<10Kformat:parquetmodality:tabularmodality:textlibrary:datasetslibrary:pandaslibrary:mlcroissantlibrary:polarsregion:us

README current version from Hugging Face


dataset_info:
features:

  • name: instruction_orig
    dtype: string
  • name: response_orig
    dtype: string
  • name: instruction
    dtype: string
  • name: response
    dtype: string
  • name: response_rejected
    dtype: string
  • name: dataset_source
    dtype: string
  • name: dataset_type
    dtype: string
  • name: orig_lang
    dtype: string
  • name: messages
    list:
    • name: content
      dtype: string
    • name: role
      dtype: string
  • name: prompt_for_judging
    dtype: string
  • name: nemotron_judging_text
    dtype: string
  • name: response_rejected_orig
    dtype: string
  • name: task_class
    dtype: string
  • name: is_multiturn
    dtype: bool
  • name: accepted_score_pairRM
    dtype: float64
  • name: rejected_score_pairRM
    dtype: float64
  • name: Ystävällisyys
    dtype: int64
  • name: Faktuaalisuus
    dtype: int64
  • name: Selkeys
    dtype: int64
  • name: Kielellinen laatu
    dtype: int64
  • name: Johdonmukaisuus
    dtype: int64
  • name: Erikoisluokittelu
    dtype: int64
  • name: Kokonaisarvosana
    dtype: float64
  • name: instruction_lang
    dtype: string
  • name: instruction_lang_score
    dtype: float64
  • name: response_lang
    dtype: string
  • name: response_lang_score
    dtype: float64
  • name: text
    dtype: string
  • name: fin_chunk_ratio_full_text
    dtype: float64
  • name: fin_10_word_chunk_amt
    dtype: int64
  • name: non_fi_10_word_chunk_amt
    dtype: int64
  • name: text_fin_chunk_ratio_bin
    dtype: int64
  • name: instruction_perplexity_kenlm
    dtype: int64
  • name: response_perplexity_kenlm
    dtype: int64
  • name: combined_perplexity
    dtype: int64
  • name: multiturn
    dtype: bool
  • name: pred_Faktuaalisuus
    dtype: float64
  • name: pred_Ystävällisyys
    dtype: float64
  • name: pred_Kielellinen laatu
    dtype: float64
  • name: pred_Selkeys
    dtype: float64
  • name: pred_Erikoisluokittelu
    dtype: float64
  • name: pred_Informatiivisuus
    dtype: float64
  • name: tok_len
    dtype: int64
  • name: quality_raw_response
    dtype: string
  • name: quality_pohdinta
    dtype: string
  • name: quality_arvio
    dtype: string
    splits:
  • name: train
    num_bytes: 97240866
    num_examples: 6680
    download_size: 42336189
    dataset_size: 97240866
    configs:
  • config_name: default
    data_files:
    • split: train
      path: data/train-*

README TO DO BUT RELEASED NEVERTHELESS

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. 2024-10-29[bot] Conversion to Parquetopen1 💬#1
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Repository

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