Datasetpublic

heispv/nanoplm-uniref50-3M-subset

NanoPLM UniRef50 3M Subset A 3,000,000-sequence subset of UniRef50 protein sequences, pre-split into train/validation sets. Sequences are filtered to a length of 20 to 512 amino acids (inclusive). Intended for pretraining and experimenting with small protein language models (PLMs). Splits Split File Sequences train train.fasta 2,950,200 validation validation.fasta 49,800 total 3,000,000 Format The dataset is provided as Parquet… See the full description on the dataset page: https://huggingface.co/datasets/heispv/nanoplm-uniref50-3M-subset.

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NanoPLM UniRef50 3M Subset

A 3,000,000-sequence subset of UniRef50 protein sequences, pre-split into train/validation sets. Sequences are filtered to a length of 20 to 512 amino acids (inclusive). Intended for pretraining and experimenting with small protein language models (PLMs).

Splits

Split	File	Sequences
train	`train.fasta`	2,950,200
validation	`validation.fasta`	49,800
total		3,000,000

Format

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:

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 (between 20 and 512, inclusive)

The original FASTA files (train.fasta, validation.fasta) are also included in the repo for direct use.

Usage

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

# Train
train_path = hf_hub_download(
    repo_id="heispv/nanoplm-uniref50-3M-subset",
    filename="train.fasta",
    repo_type="dataset",
)

# Validation
val_path = hf_hub_download(
    repo_id="heispv/nanoplm-uniref50-3M-subset",
    filename="validation.fasta",
    repo_type="dataset",
)

Source & License

Sequences are derived from UniRef50, part of the UniProt databases. UniProt data is distributed under the Creative Commons Attribution 4.0 (CC BY 4.0) license. Please cite UniProt when using this dataset:

The UniProt Consortium. UniProt: the Universal Protein Knowledgebase. Nucleic Acids Research.