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schneiderkamplab/dfm10-sapient-flan-t0-filtered-sft

dfm10-sapient-flan-t0-filtered-sft The DFM10-safe policy-selected FLAN T0 partition from the Sapient source mirror. Contents Format: gzip-compressed JSON Lines under data/train-*.jsonl.gz Schema: chat messages, optional condition and tools, plus provenance Shards: 154 Rows: 38,413,448 Category: Instruction following Upstream material sapientinc/HRM-Text-data-io-cleaned-20260515 FLAN T0 Processing Only files present in the active… See the full description on the dataset page: https://huggingface.co/datasets/schneiderkamplab/dfm10-sapient-flan-t0-filtered-sft.

sourceHugging Faceotherupdated 28d agoView on Hugging Face
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Dataset Card

dfm10-sapient-flan-t0-filtered-sft

The DFM10-safe policy-selected FLAN T0 partition from the Sapient source mirror.

Contents

  • —Format: gzip-compressed JSON Lines under data/train-*.jsonl.gz
  • —Schema: chat messages, optional condition and tools, plus provenance
  • —Shards: 154
  • —Rows: 38,413,448
  • —Category: Instruction following

Upstream material

  • —sapientinc/HRM-Text-data-io-cleaned-20260515
  • —FLAN T0

Processing

Only files present in the active filtered Sapient symlink tree are packaged. The partition boundary follows the original provenance family and retains the training-visible condition, instruction, and response fields.

Selection policy: config/data/source_filter.yaml.

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. Perform a per-family provenance, attribution, licence, privacy, and release review before upload; inclusion in an academic TDM training run does not by itself establish redistribution permission.

Validate

bash
python recreate_dataset.py