The dataset viewer is not available for this split.
Error code: JobManagerCrashedError
Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
tmax image pool
Every Apptainer/SIF image referenced by the three swerl-tmax-15k variants, stored once
and shared between them.
Read the layout from the repo, not from a prefix
The plain images are split across four directories, not one. A consumer that filters
on images/ silently gets 4,519 fewer files and then reports itself complete — the
tasks that reference the missing blobs fail later, at sandbox start, one by one.
| directory | files |
|---|---|
images/ |
9,971 |
images_b00/ |
1,933 |
images_b01/ |
2,000 |
images_b02/ |
586 |
| plain, total | 14,490 |
derived/ |
1,713 |
| total SIFs | 16,203 |
The batching exists only because HuggingFace enforces a hard limit of 10,000 files per
directory at push time; images_b00..b02 are continuations of images/ with no other
meaning. More batches may be added, so enumerate whatever directories exist rather
than hard-coding this list.
Resolve paths through task_to_blob.json instead of guessing — it already carries the
correct directory for every task.
task_to_blob.json
Keyed by variant, then by task id, valued by the blob path within this repo:
{
"original": {"task_000868_f0470dff": "images_b00/hamishi740__swerl-tmax-v3__17c682d5c609.sif", ...},
"hardened_prefilter": {...},
"solvable": {...}
}
| variant | tasks | unresolvable |
|---|---|---|
original — hamishivi/swerl-tmax-15k |
14,601 | 0 |
hardened_prefilter — wAI-org/swerl-tmax-15k-hardened-prefilter |
13,565 | 0 |
solvable — wAI-org/swerl-tmax-15k-solvable-gpt-5-6-terra |
7,015 | 0 |
Tasks outnumber blobs because distinct tasks share an image.
Plain vs derived
images*/ are the registry images unchanged — a fresh apptainer pull of the original
reference is byte-identical to the stored SIF.
derived/ are single-step derivations used by the hardened variants: an oracle file
removed, and/or the dependency the verifier imports installed, with per-task pinned
versions. A task in a hardened variant may map to either kind, so do not assume a
variant uses only one directory.
Using it
import json
from huggingface_hub import hf_hub_download, snapshot_download
m = json.load(open(hf_hub_download("wAI-org/tmax-image-pool", "task_to_blob.json",
repo_type="dataset")))
blobs = sorted(set(m["solvable"].values())) # only what this variant needs
snapshot_download("wAI-org/tmax-image-pool", repo_type="dataset",
allow_patterns=blobs, local_dir="sifs/")
Then point each row's env_config.image at the absolute local .sif path;
prefer_local_sif() passes an absolute path straight through with no registry lookup.
Fetching only one variant's blobs is much cheaper than the whole pool — solvable needs
6,968 of the 16,203.
Verifying what you fetched
Check apptainer inspect on each distinct SIF a variant references. Size and hash
agreement is not sufficient: SIFs have been seen to match both and still not be valid
squashfs. Count coverage per variant against task_to_blob.json rather than trusting a
fetcher's own "done".
- Downloads last month
- 2,210