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hyosoon0/kfold-multimer-lmdb

kfold-multimer-lmdb Training data for the multimer / protein-ligand fine-tune in hsjang0/k-fold-multimer-tuning. Pre-tokenized complexes as LMDB, plus the eval splits and label tables the configs read. Do not clone the whole thing to run one experiment. It is 201 GB and a single arm reads a handful of its sources. The repo's scripts/fetch_data.py takes a config name, works out which sources that config actually needs, and pulls only those. python scripts/fetch_data.py --config… See the full description on the dataset page: https://huggingface.co/datasets/hyosoon0/kfold-multimer-lmdb.

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kfold-multimer-lmdb

Training data for the multimer / protein-ligand fine-tune in hsjang0/k-fold-multimer-tuning. Pre-tokenized complexes as LMDB, plus the eval splits and label tables the configs read.

Do not clone the whole thing to run one experiment. It is 201 GB and a single arm reads a handful of its sources. The repo's scripts/fetch_data.py takes a config name, works out which sources that config actually needs, and pulls only those.

bash

python scripts/fetch_data.py --config CB_v7_bias4bin_v2mix_100k --dest /data/kfold

Layout

lmdb/<source>/              CA-coordinate records, 40 sources
lmdb_cb/<source>/           CB-coordinate sidecars for the sources that have one
eval_split_global/*.txt     held-out keys per source. Every config references these
stability_pairs/*.jsonl     cDNA dG pairs for the stability head

The configs expect lmdb_root to point at the lmdb/ tree and cb_root at lmdb_cb/.

The larger sources

source	size
`lmdb/afdb_homodimer_holo_pairs`	43.6 G	AFDB homodimers, holo pair schema
`lmdb/teddymer_all_holo_pairs`	37.4 G
`lmdb/sair_ligand_pairs`	27.9 G	protein-ligand, SAIR
`lmdb/afdb_synth_ligand`	16.4 G	synthetic protein-ligand
`lmdb/AFDB_Homodimer_apo_token`	16.3 G	apo tokens
`lmdb_cb/afdb_homodimer_holo_pairs`	16.5 G	CB sidecar
`lmdb/gator_affinity_pairs`	9.5 G	BindingDB Kd/Ki, cofolded
`lmdb/stability_monomer`	3.4 G	cDNA dG
`lmdb/rcsb_ligand`	3.2 G	experimental RCSB protein-ligand

What is NOT here

`monomer_80M` (607 GB) and its cluster index (3.5 GB). Deliberately excluded for size. Several configs carry nonzero weight on it, so those cannot be reproduced exactly from this repo alone. fetch_data.py names the shortfall rather than failing silently.

`homodimer_apo_holo` (52.8 GB). One data.mdb over HuggingFace's 50 GB per-file limit.

Checkpoints. Encoder weights are separate. The released TriProRep encoders are at k-fold-structure/triprorep-{35M,150M,650M,3B}.

Reading a record

python

import lmdb, pickle
env = lmdb.open("lmdb/rcsb_holo_pairs", readonly=True, lock=False)
with env.begin() as txn:
    rec = pickle.loads(txn.next())

lock.mdb is a runtime lock and is deliberately not included; lmdb.open(..., lock=False) does not need it.

Provenance

Every source was built by a script in the GitHub repo, listed in its CODEMAP.md section 4, and described in DATASET.md. Eval keys are held out by sequence identity at the AlphaFold-Multimer interface-level convention, not by random assignment.