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jbross-ibm-research/M-IFEval

published by @jbross-ibm-research

Alignment dataset tracked in the /datasets sub-catalog.

Lifetime downloads
271
Last 30 days
16
Likes
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Size
221 KB
Created on HF
2026-03-12
Age
7 months ago

Tags

size_categories:1K<n<10Kformat:parquetformat:optimized-parquetmodality:textlibrary:datasetslibrary:pandaslibrary:polarslibrary:mlcroissantregion:us

README current version from Hugging Face


dataset_info:

  • config_name: en
    features:
    • name: key
      dtype: int64
    • name: prompt
      dtype: string
    • name: instruction_id_list
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      • name: capital_relation
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      • name: keywords
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      • name: num_paragraphs
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      • name: language
        dtype: string
      • name: let_relation
        dtype: string
      • name: letter
        dtype: string
      • name: let_frequency
        dtype: int64
      • name: end_phrase
        dtype: string
      • name: forbidden_words
        list: string
      • name: keyword
        dtype: string
      • name: frequency
        dtype: int64
      • name: num_sentences
        dtype: int64
      • name: postscript_marker
        dtype: string
      • name: first_word
        dtype: string
      • name: nth_paragraph
        dtype: int64
        splits:
    • name: train
      num_bytes: 284485
      num_examples: 541
      download_size: 93253
      dataset_size: 284485
  • config_name: es
    features:
    • name: key
      dtype: int64
    • name: prompt
      dtype: string
    • name: instruction_id_list
      list: string
    • name: kwargs
      list:
      • name: keywords
        list: string
      • name: num_bullets
        dtype: int64
      • name: relation
        dtype: string
      • name: num_words
        dtype: int64
      • name: capital_relation
        dtype: string
      • name: capital_frequency
        dtype: int64
      • name: language
        dtype: string
      • name: let_relation
        dtype: string
      • name: letter
        dtype: string
      • name: let_frequency
        dtype: int64
      • name: keyword
        dtype: string
      • name: frequency
        dtype: int64
      • name: num_paragraphs
        dtype: int64
      • name: num_placeholders
        dtype: int64
      • name: end_phrase
        dtype: string
      • name: num_sentences
        dtype: int64
      • name: forbidden_words
        list: string
      • name: section_spliter
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      • name: num_sections
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      • name: first_word
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      • name: nth_paragraph
        dtype: int64
      • name: num_highlights
        dtype: int64
      • name: postscript_marker
        dtype: string
      • name: prompt_to_repeat
        dtype: string
        splits:
    • name: train
      num_bytes: 48121
      num_examples: 115
      download_size: 28446
      dataset_size: 48121
  • config_name: fr
    features:
    • name: key
      dtype: int64
    • name: prompt
      dtype: string
    • name: instruction_id_list
      list: string
    • name: kwargs
      list:
      • name: capital_frequency
        dtype: int64
      • name: capital_relation
        dtype: string
      • name: prompt_to_repeat
        dtype: string
      • name: num_placeholders
        dtype: int64
      • name: postscript_marker
        dtype: string
      • name: section_spliter
        dtype: string
      • name: num_sections
        dtype: int64
      • name: num_bullets
        dtype: int64
      • name: num_highlights
        dtype: int64
      • name: keywords
        list: string
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        list: string
      • name: keyword
        dtype: string
      • name: frequency
        dtype: int64
      • name: relation
        dtype: string
      • name: letter
        dtype: string
      • name: let_frequency
        dtype: int64
      • name: let_relation
        dtype: string
      • name: language
        dtype: string
      • name: num_paragraphs
        dtype: int64
      • name: nth_paragraph
        dtype: int64
      • name: first_word
        dtype: string
      • name: num_sentences
        dtype: int64
      • name: num_words
        dtype: int64
      • name: word_to_accentuate
        struct:
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        • name: celebrites
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        • name: generations
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        • name: a
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        • name: ecole
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        • name: tot
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        • name: methodes
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        • name: preferees
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        • name: acquerir
          dtype: string
        • name: competence
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        • name: deja
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        • name: redigez
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        • name: reseaux
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        • name: oranges
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        • name: ete
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        • name: leger
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      • name: forbidden_char
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        dtype: string
        splits:
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      num_examples: 235
      download_size: 57693
      dataset_size: 151055
  • config_name: ja
    features:
    • name: key
      dtype: int64
    • name: prompt
      dtype: string
    • name: instruction_id_list
      list: string
    • name: kwargs
      list:
      • name: language
        dtype: string
      • name: relation
        dtype: string
      • name: num_sentences
        dtype: int64
      • name: num_placeholders
        dtype: int64
      • name: num_bullets
        dtype: int64
      • name: num_items
        dtype: int64
      • name: num_highlights
        dtype: int64
      • name: section_spliter
        dtype: string
      • name: num_sections
        dtype: int64
      • name: num_paragraphs
        dtype: int64
      • name: postscript_marker
        dtype: string
      • name: keywords
        list: string
      • name: keyword
        dtype: string
      • name: frequency
        dtype: int64
      • name: num_letters
        dtype: int64
      • name: first_word
        dtype: string
      • name: nth_paragraph
        dtype: int64
      • name: forbidden_words
        list: string
      • name: prompt_to_repeat
        dtype: string
      • name: end_phrase
        dtype: string
      • name: let_relation
        dtype: string
      • name: letter
        dtype: string
      • name: let_frequency
        dtype: int64
      • name: kanji_limit
        dtype: int64
      • name: ending
        dtype: string
      • name: count
        dtype: int64
        splits:
    • name: train
      num_bytes: 88795
      num_examples: 172
      download_size: 38129
      dataset_size: 88795
      configs:
  • config_name: en
    data_files:
    • split: train
      path: en/train-*
  • config_name: es
    data_files:
    • split: train
      path: es/train-*
  • config_name: fr
    data_files:
    • split: train
      path: fr/train-*
  • config_name: ja
    data_files:
    • split: train
      path: ja/train-*

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. 2026-03-12Upload dataset07d24b26.5 KB
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  3. 2026-03-12Upload datasetdd5d8172.8 KB
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  4. 2026-03-12Upload datasetf47dbb81.4 KB
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  5. 2026-03-12initial commit8d058160 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. 2026-03-13[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("jbross-ibm-research/M-IFEval")
Raw snapshot (Python)
from huggingface_hub import snapshot_download
snapshot_download(repo_id="jbross-ibm-research/M-IFEval", repo_type="dataset")
git clone (requires git-lfs)
git clone https://huggingface.co/datasets/jbross-ibm-research/M-IFEval
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