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README.md

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 ---
-license: mit
+license: cc-by-4.0
+pretty_name: NanoPLM UniRef50 3M Subset
+language:
+  - en
+tags:
+  - biology
+  - protein
+  - proteins
+  - uniref
+  - uniref50
+  - protein-language-model
+  - bioinformatics
+size_categories:
+  - 1M<n<10M
 ---
+
+# NanoPLM UniRef50 3M Subset
+
+A 3,000,000-sequence subset of [UniRef50](https://www.uniprot.org/help/uniref) protein
+sequences, pre-split into train/validation sets. Intended for pretraining and
+experimenting with small protein language models (PLMs).
+
+## Splits
+
+| Split | File          | Sequences |
+| ----- | ------------- | --------: |
+| train | `train.fasta` | 2,950,200 |
+| val   | `val.fasta`   |    49,800 |
+| **total** |           | **3,000,000** |
+
+## Format
+
+Standard FASTA. Each record is a UniRef50 cluster representative — the header is the
+original UniRef50 description line, followed by the amino-acid sequence:
+
+```
+>UniRef50_A0A4Y2FNR1 STPR domain-containing protein n=2 Tax=Araneus ventricosus TaxID=182803 RepID=A0A4Y2FNR1_ARAVE
+MGSSSTHLCRLGHGQLIQMPSSVLIIRFNHGTLNYGIQYGVRSIKEKGVTGEAARRQQPITKRERRVAETDEERND...
+```
+
+## Usage
+
+Download the split files directly with the Hugging Face Hub client:
+
+```python
+from huggingface_hub import hf_hub_download
+
+train_path = hf_hub_download(
+    repo_id="heispv/nanoplm-uniref50-3M-subset",
+    filename="train.fasta",
+    repo_type="dataset",
+)
+val_path = hf_hub_download(
+    repo_id="heispv/nanoplm-uniref50-3M-subset",
+    filename="val.fasta",
+    repo_type="dataset",
+)
+```
+
+Parse the FASTA (e.g. with Biopython):
+
+```python
+from Bio import SeqIO
+
+for record in SeqIO.parse(train_path, "fasta"):
+    seq_id = record.id          # e.g. "UniRef50_A0A4Y2FNR1"
+    sequence = str(record.seq)
+    ...
+```
+
+## Source & License
+
+Sequences are derived from UniRef50, part of the
+[UniProt](https://www.uniprot.org/) databases. UniProt data is distributed under the
+[Creative Commons Attribution 4.0 (CC BY 4.0)](https://creativecommons.org/licenses/by/4.0/)
+license. Please cite UniProt when using this dataset:
+
+> The UniProt Consortium. *UniProt: the Universal Protein Knowledgebase.*
+> Nucleic Acids Research.