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README.md

@@ -1,8 +1,6 @@
 ---
 license: cc-by-4.0
 pretty_name: NanoPLM UniRef50 3M Subset
-language:
-  - en
 tags:
   - biology
   - protein
@@ -13,6 +11,13 @@ tags:
   - bioinformatics
 size_categories:
   - 1M<n<10M
+configs:
+  - config_name: default
+    data_files:
+      - split: train
+        path: data/train-*.parquet
+      - split: validation
+        path: data/validation-*.parquet
 ---
 
 # NanoPLM UniRef50 3M Subset
@@ -31,17 +36,43 @@ experimenting with small protein language models (PLMs).
 
 ## Format
 
-Standard FASTA. Each record is a UniRef50 cluster representative — the header is the
-original UniRef50 description line, followed by the amino-acid sequence:
+The dataset is provided as **Parquet** (powers the Dataset Viewer and `load_dataset`).
+Each row is a UniRef50 cluster representative with the header parsed into columns:
 
-```
->UniRef50_A0A4Y2FNR1 STPR domain-containing protein n=2 Tax=Araneus ventricosus TaxID=182803 RepID=A0A4Y2FNR1_ARAVE
-MGSSSTHLCRLGHGQLIQMPSSVLIIRFNHGTLNYGIQYGVRSIKEKGVTGEAARRQQPITKRERRVAETDEERND...
-```
+| Column     | Type   | Description                                            |
+| ---------- | ------ | ------------------------------------------------------ |
+| `id`       | string | UniRef50 cluster ID, e.g. `UniRef50_A0A4Y2FNR1`        |
+| `name`     | string | Cluster name / protein description                     |
+| `n`        | int64  | Number of members in the cluster (`n=` field)          |
+| `tax`      | string | Lowest common taxon (`Tax=` field)                     |
+| `tax_id`   | string | NCBI taxonomy ID (`TaxID=` field)                      |
+| `rep_id`   | string | Representative member ID (`RepID=` field)              |
+| `sequence` | string | Amino-acid sequence                                    |
+| `length`   | int64  | Sequence length                                        |
+
+The original **FASTA** files (`train.fasta`, `val.fasta`) are also included in the repo
+for direct use.
 
 ## Usage
 
-Download the split files directly with the Hugging Face Hub client:
+Load with the 🤗 `datasets` library:
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("heispv/nanoplm-uniref50-3M-subset")
+print(ds)                       # DatasetDict with 'train' and 'validation'
+print(ds["train"][0]["sequence"])
+
+# Stream without downloading everything:
+ds = load_dataset("heispv/nanoplm-uniref50-3M-subset", split="train", streaming=True)
+for ex in ds:
+    seq = ex["sequence"]
+    ...
+    break
+```
+
+Or download the raw FASTA files directly:
 
 ```python
 from huggingface_hub import hf_hub_download
@@ -51,22 +82,6 @@ train_path = hf_hub_download(
     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