dataset_name string | format string | msdatasets_min_version string | shard_count int64 | total_size int64 | shards list |
|---|---|---|---|---|---|
consensus_100M | mszx | TODO | 90 | 140,420,720,640 | [
{
"name": "consensus_00.mszx",
"size": 1556203520,
"sha256": "dda3814d59456907b631ed95f9f685447449b9f7065d6003c04c79ffa183e84b"
},
{
"name": "consensus_01.mszx",
"size": 1591838720,
"sha256": "c14cb5672190e7d7d73af180c7b1f49a904481bcc83c01986ffeb5f6f42072e8"
},
{
"name": "consens... |
Consensus 100M (mszx)
A 100M-scale mass spectrometry consensus dataset, distributed as mszx
archive shards for use with the msdatasets
library.
Contents
- 90 shards:
consensus_00.mszx...consensus_89.mszx - ~1.5 GB per shard, ~140 GB total
manifest.json— shard list with sizes and sha256 checksumsSHA256SUMS—sha256sum-format file for direct verification
The shards are independent; row order across shards is not meaningful.
Loading with msdatasets
The Hugging Face download path will land in
msdatasetsshortly. Until then, shards can be fetched directly withhuggingface_huband pointed at any existingmsdatasetsmszxreader.
Once the HF source is wired up, usage will look like:
from msdatasets import download_dataset
ds = download_dataset("hf://chrisagrams/consensus-100M-mszx", store_as="mszx")
Manual download
from huggingface_hub import snapshot_download
local_dir = snapshot_download(
repo_id="chrisagrams/consensus-100M-mszx",
repo_type="dataset",
allow_patterns=["*.mszx", "manifest.json", "SHA256SUMS"],
)
Verify integrity:
cd "$local_dir" && sha256sum -c SHA256SUMS
Format
mszx is the raw archive format produced by the msdatasets server. See the
msdatasets documentation for the
spec and reader implementation.
Citation
TODO
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