misc 0 0 0

schneiderkamplab/dfm10-mimir-ifeval-verifier-sft

published by @schneiderkamplab

Alignment dataset tracked in the /datasets sub-catalog.

Lifetime downloads
67
Last 30 days
30
Likes
-
Size
66.3 MB
Created on HF
2026-08-31
Age
1 months ago

Description

dfm10-mimir-ifeval-verifier-sft

Verifier-backed instruction-following examples grounded in licensed source passages.

Contents

Format: gzip-compressed JSON Lines under data/train-*.jsonl.gz

Schema: chat messages, optional condition and tools, plus provenance

Shards: 1

Rows: 163,635

Category: Instruction following

Upstream material

Novel verifier-backed synthetic instruction tasks

Processing

Gemma 4 31B generated candidates;… See the full description on the dataset page: https://huggingface.co/datasets/schneiderkamplab/dfm10-mimir-ifeval-verifier-sft.

Tags

language:dalanguage:enlicense:otherregion:usinstruction-tuningchatdfm10repaired

README current version from Hugging Face


license: other
language:

  • da
  • en
    tags:
  • instruction-tuning
  • chat
  • dfm10
  • repaired
    pretty_name: dfm10-mimir-ifeval-verifier-sft

dfm10-mimir-ifeval-verifier-sft

Verifier-backed instruction-following examples grounded in licensed source passages.

Contents

  • Format: gzip-compressed JSON Lines under data/train-*.jsonl.gz
  • Schema: chat messages, optional condition and tools, plus provenance
  • Shards: 1
  • Rows: 163,635
  • Category: Instruction following

Upstream material

  • Novel verifier-backed synthetic instruction tasks

Processing

Gemma 4 31B generated candidates; deterministic constraint verification, independent five-dimension audit, exact decontamination, deduplication, and a 4,096-token cap were applied.

Selection policy: all rows in the packaged source artifact.

Every packaged row is taken from the accepted source tree identified in the
package manifest. Tokenized arrays and epoch sampling indices are not included;
export staging alone does not imply inclusion in a sampled training union.

License and release review

This package does not replace or broaden the licenses of its upstream materials. Review the dataset card, preserve upstream notices and attribution, and record the release decision before upload. Preserve row-level source provenance and upstream license metadata.

Validate

python recreate_dataset.py

README history 2 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. 2026-08-31Add files using upload-large-folder toold3c8f6d1.4 KB
    Loading...
  2. 2026-08-31initial commita8ae55f0 B
    Loading...

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.

Related datasets same stage · misc

Read further

Metadata

License
other

Repository

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("schneiderkamplab/dfm10-mimir-ifeval-verifier-sft")
Raw snapshot (Python)
from huggingface_hub import snapshot_download
snapshot_download(repo_id="schneiderkamplab/dfm10-mimir-ifeval-verifier-sft", repo_type="dataset")
git clone (requires git-lfs)
git clone https://huggingface.co/datasets/schneiderkamplab/dfm10-mimir-ifeval-verifier-sft
Catalog is the map. Apps are the tools.

Run models on your own machine, not in the cloud.

Every model page has an "Open in Abliteration" button that hands the model directly to the first-party desktop client, at the quantization your rig can actually run. No API keys, no subscription, no prompt leakage.

Open in Abliteration