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agentlans/drill

published by @agentlans

Alignment dataset tracked in the /datasets sub-catalog.

Lifetime downloads
1.6K
Last 30 days
94
Likes
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Size
237.5 MB
Created on HF
2025-04-16
Age
1 years ago

Description

Drill

This dataset combines multiple instruction-following datasets:

argilla/ifeval-like-data (filtered subset)

ArliAI/Formax-v1.0

ChristianAzinn/json-training

HuggingFaceH4/ifeval-like-data

allenai/tulu-3-sft-personas-instruction-following

nvidia/Nemotron-Instruction-Following-Chat-v1 structured_output split

It contains prompts with detailed instructions and corresponding formatted outputs, suitable for training models on instruction adherence and structured text… See the full description on the dataset page: https://huggingface.co/datasets/agentlans/drill.

Tags

language:enlicense:apache-2.0size_categories:100K<n<1Mformat:jsonmodality:textlibrary:datasetslibrary:pandaslibrary:polarslibrary:mlcroissantregion:usifevalformattingstructured-outputinstruction-followingtext-generation

README current version from Hugging Face

language:

  • en
    tags:
  • ifeval
  • formatting
  • structured-output
  • instruction-following
  • text-generation
    configs:
  • config_name: train
    data_files:
    • path:
      • train.jsonl.zst
        split: train
        default: true
  • config_name: ifeval-like
    data_files:
    • path:
      • ifeval-like.jsonl.zst
        split: train
  • config_name: Formax
    data_files:
    • path:
      • Formax.jsonl.zst
        split: train
  • config_name: json-training
    data_files:
    • path:
      • json-training.jsonl.zst
        split: train
  • config_name: HuggingFace-ifeval-like
    data_files:
    • path:
      • HuggingFace-ifeval.jsonl.zst
        split: train
  • config_name: tulu-3-sft-personas-instruction-following
    data_files:
    • path:
      • tulu3-persona-following.jsonl.zst
        split: train
  • config_name: Nemotron-Instruction-Following-Chat-v1
    data_files:
    • path:
      • Nemotron-Instruction-Following-Chat-v1.jsonl.zst
        split: train
        license: apache-2.0

Drill

This dataset combines multiple instruction-following datasets:

It contains prompts with detailed instructions and corresponding formatted outputs, suitable for training models on instruction adherence and structured text generation.

Definition of the word "drill" according to Merriam-Webster Dictionary

drill (noun)

  • a physical or mental exercise aimed at perfecting facility and skill especially by regular practice
  • a formal exercise by a team of marchers
  • the approved, correct, or usual procedure for accomplishing something : routine

Data Composition

Dataset Rows Included
ifeval-like 56 339
json-training 20 644
Formax-v1.0 456 361
HuggingFace-ifeval-like 5 514
tulu-3-sft-personas-instruction-following 29 980
Nemotron-Instruction-Following-Chat-v1 4 969
Train 115 127

Train contains a maximum of 28 000 rows from each dataset.

Fields

  • input: Full prompt including instructions and formatting requirements.
  • output: Sample answer that meets the prompt criteria.
  • source: The original dataset.

Usage

Ideal for training and evaluating instruction-following language models with complex output formatting.

Citation

Please cite the original datasets:

README history 11 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. 2026-02-25Licence4bf3dd33.7 KB
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  2. 2026-02-25Add Nemotron dataset5e4338a3.7 KB
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  3. 2025-08-22Update README.mdf453aae3.2 KB
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  4. 2025-08-22Upload train.jsonl.zst0e457873 KB
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  6. 2025-08-22Upload 2 files205901a2.4 KB
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  7. 2025-04-16Update README.mde07502d2.4 KB
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  8. 2025-04-16Update README.md2eacab92.1 KB
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  9. 2025-04-16Upload 4 files15c7348503 B
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  10. 2025-04-16Create README.md109e59b503 B
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  11. 2025-04-16initial commitae3246d0 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. 2025-04-17[bot] Conversion to Parquetopen1 💬#1
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Read further

Community best practices (evaluation)
4 rules on judges, benchmarks, and reporting.
Reference-set drift over time
Why the same benchmark means different things across model generations.
How we label the method for each model
The 12 classification rules that assign M1-M8 to every model.
Non-English abliteration communities
The Korean scepticism about one-click tools and non-English benchmark blindspots.

Metadata

License
apache-2.0

Repository

FILE .gitattributes FILE Formax.jsonl.zst FILE HuggingFace-ifeval.jsonl.zst FILE ifeval-like.jsonl.zst FILE json-training.jsonl.zst FILE Nemotron-Instruction-Following-Chat-v1.jsonl.zst FILE README.md FILE train.jsonl.zst FILE tulu3-persona-following.jsonl.zst

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("agentlans/drill")
Raw snapshot (Python) 
from huggingface_hub import snapshot_download
snapshot_download(repo_id="agentlans/drill", repo_type="dataset")
git clone (requires git-lfs) 
git clone https://huggingface.co/datasets/agentlans/drill
Browse repository on Hugging Face ->
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