Add README with subset configs

README.md

@@ -1,4 +1,15 @@
 ---
+license: other
+task_categories:
+  - text-generation
+tags:
+  - biology
+  - genomics
+  - dna
+  - pretraining
+  - carbon
+  - parquet
+pretty_name: Carbon pretraining corpus
 configs:
   - config_name: eukaryote_generator
     data_files:
@@ -20,32 +31,119 @@ configs:
 
 # Carbon pretraining corpus
 
-Private aggregation of the four sources used for Carbon pure-DNA pretraining,
-all stored as parquet for direct `load_dataset` access.
+Private aggregation of the DNA-side sources used for Carbon pretraining, mirrored
+into one Hub dataset with four loadable configs. The goal is to make the
+pretraining mixture reproducible without re-stitching data from multiple upstream
+repositories.
+
+All files are stored as Parquet. OpenGenome2 JSONL sources were converted to
+Parquet and their `metadata.file_path` values were scrubbed so the metadata keeps
+only useful upstream provenance such as `{"source": "data_mrna_train_chunk1.jsonl.gz"}`
+and, where present, the upstream `record` id.
 
 ## 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 |
+| Config | Upstream source | Files | Size | Rows / sequence stats |
+|---|---:|---:|---:|---|
+| `eukaryote_generator` | [GenerTeam/pretrain_data_eukaryote](https://huggingface.co/datasets/GenerTeam/pretrain_data_eukaryote) | 456 | 376.80 GB | Rich schema with `sequence`, `taxonomy`, `species_type`, `gene_type`, coordinates, and boundary markers. A sampled fungi shard has 187,500 rows with mean sequence length ~1,631 nt. |
+| `mrna_evo2` | [OpenGenome2 mRNA](https://huggingface.co/datasets/arcinstitute/opengenome2/tree/main/json/pretraining_or_both_phases/mrna) | 11 | 54.78 GB | 52,702,454 rows; 115.94 Gbp total; mean 2,200 nt; min 64; max 99,994. |
+| `mrna_splice_evo2` | [OpenGenome2 mRNA splice/promoter](https://huggingface.co/datasets/arcinstitute/opengenome2/tree/main/json/pretraining_or_both_phases/mrna_splice_promoter) | 19 | 92.89 GB | 56,877,762 rows; 197.36 Gbp total; mean 3,470 nt; min 96; max 122,533. |
+| `prokaryote_evo2` | [OpenGenome2 GTDB v220 + IMG/PR](https://huggingface.co/datasets/arcinstitute/opengenome2/tree/main/json/pretraining_or_both_phases/gtdb_v220_imgpr) | 34 | 165.98 GB | 17,408,059 rows; 357.45 Gbp total; mean 20,533 nt; min 20; max 16,040,666. |
 
 Test splits from opengenome2 are not included (this is a pretraining corpus).
 
+## Schema
+
+`eukaryote_generator` preserves the GenerTeam Parquet schema:
+
+```text
+begin_of_sequence, end_of_sequence, begin_of_gene, end_of_gene, gene_type,
+species_type, strand, sequence, molecule_type, topology, taxonomy, record_id,
+start, end
+```
+
+The three OpenGenome2-derived configs have:
+
+```text
+text, metadata
+```
+
+After scrubbing, `metadata` no longer contains local `/scratch/...` paths. It
+contains a compact upstream source filename, and for prokaryote rows may also
+include `record`.
+
 ## Usage
 
 ```python
 from datasets import load_dataset
 
-# pick any subset
-ds = load_dataset("hf-carbon/carbon-pretraining-corpus", "mrna_evo2", split="train", streaming=True)
+ds = load_dataset(
+    "hf-carbon/carbon-pretraining-corpus",
+    "mrna_evo2",
+    split="train",
+    streaming=True,
+)
 print(next(iter(ds)))
 ```
 
-## License
+To stream the four configs together:
+
+```python
+from datasets import interleave_datasets, load_dataset
+
+configs = [
+    "eukaryote_generator",
+    "prokaryote_evo2",
+    "mrna_splice_evo2",
+    "mrna_evo2",
+]
+streams = [
+    load_dataset("hf-carbon/carbon-pretraining-corpus", cfg, split="train", streaming=True)
+    for cfg in configs
+]
+mixed = interleave_datasets(streams, seed=42)
+```
 
-Defer to upstream sources:
-- GenerTeam/pretrain_data_eukaryote — see upstream repo.
-- arcinstitute/opengenome2 — see upstream repo.
+Pass `probabilities=` to `interleave_datasets` if you want to reproduce a
+specific training mixture.
+
+## Provenance
+
+This mirror is derived from:
+
+- [GenerTeam/pretrain_data_eukaryote](https://huggingface.co/datasets/GenerTeam/pretrain_data_eukaryote), MIT license.
+- [arcinstitute/opengenome2](https://huggingface.co/datasets/arcinstitute/opengenome2), Apache-2.0 license.
+
+The OpenGenome2 configs include train chunks only:
+
+- `json/pretraining_or_both_phases/mrna/*_train_*.jsonl.gz`
+- `json/pretraining_or_both_phases/mrna_splice_promoter/*_train_*.jsonl.gz`
+- `json/pretraining_or_both_phases/gtdb_v220_imgpr/*_train_*.jsonl.gz`
+
+## Limitations
+
+- This is a private pretraining mirror, not a benchmark dataset.
+- OpenGenome2 test chunks are intentionally omitted.
+- No additional deduplication or quality filtering was applied beyond upstream processing.
+- The configs are schema-asymmetric: `eukaryote_generator` has a rich structured schema, while OpenGenome2-derived configs are `text` plus `metadata`.
+- Sequence casing, ambiguity codes, and length distributions differ by upstream source.
+
+## Citation
+
+If you use this mirror, cite the upstream datasets:
+
+```bibtex
+@misc{generteam2025generator,
+  title        = {GENERATOR: A Long-Context Generative Genomic Foundation Model},
+  author       = {GenerTeam},
+  year         = {2025},
+  eprint       = {2502.07272},
+  archivePrefix= {arXiv},
+}
+
+@misc{arcinstitute_opengenome2,
+  title        = {OpenGenome2},
+  author       = {Arc Institute},
+  howpublished = {Hugging Face dataset: arcinstitute/opengenome2},
+}
+```