BFD Source Archive Index

This dataset contains the original BFD source archive plus a viewer-friendly compressed byte-range index. The source archive is about 292 GB, so the default Dataset Viewer table is an index over 1 GiB compressed chunks rather than a fully expanded sequence table.

Use the original bfd_metaclust_clu_complete_id30_c90_final_seq.sorted_opt.tar.gz archive for complete sequence data. Use the default Parquet table for quick inspection, Dataset Viewer previews, and source-size/chunk metadata.

Splits

The split is deterministic by chunk identifier: sha256(index_id) % 10. Bucket 0 is test; buckets 1 through 9 are train.

Split	Rows
train	255
test	17
total	272

Source File

File	Size
bfd_metaclust_clu_complete_id30_c90_final_seq.sorted_opt.tar.gz	291,649,557,441 bytes

Usage

pip install datasets

Load the archive index:

from datasets import load_dataset

ds = load_dataset("LiteFold/BFD")
print(ds)
print(ds["train"][0])

Load one split:

from datasets import load_dataset

train = load_dataset("LiteFold/BFD", split="train")
test = load_dataset("LiteFold/BFD", split="test")

Download the original archive:

from huggingface_hub import hf_hub_download

archive_path = hf_hub_download(
    repo_id="LiteFold/BFD",
    repo_type="dataset",
    filename="bfd_metaclust_clu_complete_id30_c90_final_seq.sorted_opt.tar.gz",
)

Load the source-file manifest:

import pandas as pd
from huggingface_hub import hf_hub_download

path = hf_hub_download(
    repo_id="LiteFold/BFD",
    repo_type="dataset",
    filename="metadata/source_files.parquet",
)
source_files = pd.read_parquet(path)
print(source_files)

Columns

Column	Description
index_id	Stable row ID for one compressed chunk.
repo_id	Hugging Face dataset repository.
source_file	Source archive filename.
source_sha	Source repository commit used to build the index.
source_format	Source archive format.
chunk_index	Zero-based compressed chunk index.
byte_start	Inclusive compressed byte offset.
byte_end_exclusive	Exclusive compressed byte offset.
chunk_size_bytes	Compressed chunk size in bytes.
total_size_bytes	Full compressed archive size.
chunk_size_gib	Target chunk size in GiB.
is_first_chunk	Whether the row indexes the first chunk.
is_last_chunk	Whether the row indexes the final chunk.
access_note	Note describing the index scope.
split_bucket	Deterministic split bucket from sha256(index_id) % 10.

Preparation

The normalization script used to create the Parquet files is included at scripts/prepare_bfd_dataset.py.