| --- |
| license: cc-by-4.0 |
| language: |
| - en |
| - zh |
| size_categories: |
| - 100K<n<1M |
| task_categories: |
| - text-generation |
| - question-answering |
| tags: |
| - biology |
| - protein |
| - DNA |
| - bioinformatics |
| --- |
| |
| # OmniGene-4 SFT corpus |
|
|
| Supervised fine-tuning data for the OmniGene-4 / OmniGene-4-MM family. |
| See https://github.com/maris205/omnigene4 for the training scripts that |
| consume these files. |
|
|
| ## Files |
|
|
| | File | Rows | Used by | Description | |
| |---|---|---|---| |
| | `bio_sft_v2_train.jsonl` | ~179K | Bio-SFT v2 | Eight task families: protein homology (BioPAWS), DNA, structure (3Di/DSSP), cell biology, molecules, mutation, structure prediction, general bio QA | |
| | `distill_seed.jsonl` | ~6K | seed-only | Initial distillation seed used to bootstrap the v2 corpus | |
| | `train/omnigene_sft_v1_train.jsonl` | ~179K | SFT v3 base | Same as v2 with cleaner schema and Alpaca template | |
| | `train/omnigene_sft_v1_train_with_remote.jsonl` | **~199K** | **SFT v3-v5 (final)** | Above + 20K BioPAWS `protein_pair_remote` rows; this is the file used by Bio-SFT v3, v4, v5, and the OmniGene-4-MM Stage 2/3 LoRA training | |
| | `eval/omnigene_sft_v1_eval.jsonl` | ~1.5K | held-out eval | Used by `40-eval_omnigene4mm.py`, `60-eval_stage2.py`, `92-eval_stage3v3.py`, etc. | |
| | `master/omnigene_sft_v1_master.jsonl` | ~285K | (intermediate) | Pre-split master corpus before train/eval split | |
| | `master/cell_sft_master.jsonl` | ~37K | task subset | Cell-biology SFT subset | |
| | `master/mol_sft_master.jsonl` | ~50K | task subset | Molecule SFT subset | |
| | `stats/data_mix_report.json` | — | metadata | Per-category counts and ratios | |
|
|
| ## Schema |
|
|
| Each line is a JSON object with at least `instruction`, `input`, `output`, |
| and `category`. Some rows additionally carry `task_name` and `subtask` for |
| fine-grained accounting. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @article{wang2026omnigene4, |
| author = {Wang, Liang}, |
| title = {{OmniGene-4}: A Unified Bio-Language MoE Model with Router-Level |
| Interpretability and Modality-Invariant Transfer}, |
| year = {2026}, |
| journal = {bioRxiv}, |
| doi = {10.64898/2026.05.12.724542} |
| } |
| ``` |
|
|
