---
configs:
  - config_name: eukaryote_generator
    data_files:
      - split: train
        path: eukaryote_generator/**/*.parquet
  - config_name: mrna_evo2
    data_files:
      - split: train
        path: mrna_evo2/*.parquet
  - config_name: mrna_splice_evo2
    data_files:
      - split: train
        path: mrna_splice_evo2/*.parquet
  - config_name: prokaryote_evo2
    data_files:
      - split: train
        path: prokaryote_evo2/*.parquet
---

# Carbon pretraining corpus

Private aggregation of the four sources used for Carbon pure-DNA pretraining,
all stored as parquet for direct `load_dataset` access.

## Subsets

| Subset | Source | Description |
|---|---|---|
| `eukaryote_generator` | [GenerTeam/pretrain_data_eukaryote](https://huggingface.co/datasets/GenerTeam/pretrain_data_eukaryote) | Eukaryote DNA, sharded by species (`fungi/`, `plants/`, `protozoa/`, `vertebrate_mammalian/`, ...) |
| `mrna_evo2` | [arcinstitute/opengenome2 / mrna](https://huggingface.co/datasets/arcinstitute/opengenome2/tree/main/json/pretraining_or_both_phases/mrna) | mRNA sequences, train chunks only |
| `mrna_splice_evo2` | [arcinstitute/opengenome2 / mrna_splice_promoter](https://huggingface.co/datasets/arcinstitute/opengenome2/tree/main/json/pretraining_or_both_phases/mrna_splice_promoter) | mRNA + splice + promoter, train chunks only |
| `prokaryote_evo2` | [arcinstitute/opengenome2 / gtdb_v220_imgpr](https://huggingface.co/datasets/arcinstitute/opengenome2/tree/main/json/pretraining_or_both_phases/gtdb_v220_imgpr) | Prokaryote (GTDB v220 + IMG/PR), train chunks only |

Test splits from opengenome2 are not included (this is a pretraining corpus).

## Usage

```python
from datasets import load_dataset

# pick any subset
ds = load_dataset("hf-carbon/carbon-pretraining-corpus", "mrna_evo2", split="train", streaming=True)
print(next(iter(ds)))
```

## License

Defer to upstream sources:
- GenerTeam/pretrain_data_eukaryote — see upstream repo.
- arcinstitute/opengenome2 — see upstream repo.