The dataset viewer is not available for this subset.
Exception: SplitsNotFoundError
Message: The split names could not be parsed from the dataset config.
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
for split_generator in builder._split_generators(
~~~~~~~~~~~~~~~~~~~~~~~~~^
StreamingDownloadManager(base_path=builder.base_path, download_config=download_config)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 81, in _split_generators
first_examples = list(islice(pipeline, self.NUM_EXAMPLES_FOR_FEATURES_INFERENCE))
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 32, in _get_pipeline_from_tar
fs: fsspec.AbstractFileSystem = fsspec.filesystem("memory")
~~~~~~~~~~~~~~~~~^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/fsspec/registry.py", line 302, in filesystem
cls = get_filesystem_class(protocol)
File "/usr/local/lib/python3.14/site-packages/fsspec/registry.py", line 239, in get_filesystem_class
raise ValueError(f"Protocol not known: {protocol}")
ValueError: Protocol not known: memory
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 71, in compute_split_names_from_streaming_response
for split in get_dataset_split_names(
~~~~~~~~~~~~~~~~~~~~~~~^
path=dataset,
^^^^^^^^^^^^^
config_name=config,
^^^^^^^^^^^^^^^^^^^
token=hf_token,
^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
info = get_dataset_config_info(
path,
...<6 lines>...
**config_kwargs,
)
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.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.
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
h200-nav-eval-exchange
Cross-checking two boxes' open-loop evaluation of the pooled move to run. Everything here
is raw physical units (m/s, rad/s), full 32-step chunk, denoise 10, seed 0.
h200_nav_preds_d1.npz (H200 box, 1 draw)
targets (512, 32, 23)
pred::init (pre-SFT)
pred::SFT-50k (LoRA)
pred::nav (pooled) step-30000
frame::dataset_index index into the eval dataset (0..107,024)
frame::source_episode_index original episode, 0..199
frame::source_start_frame segment start in that episode
frame::frame_in_episode offset inside the segment
# absolute source frame = source_start_frame + frame_in_episode
Frame ids were reconstructed from the seed (numpy rng.choice, not a DataLoader shuffle)
and then VERIFIED by re-reading the dataset at those indices: 9/9 sampled rows match the
stored targets to 1.2e-08. The other box's seed reconstruction failed and was redone by
fingerprinting; ours reproduces because the picks are drawn directly in main().
Scored with pi05_b1k_pytorch_local + pi05-b1k-sft50k-merged/assets for init and SFT-50k
(turning_on_radio z-score) and pi05_b1k_nav + its own assets (quantile) for nav, then
converted back to physical units per model — R² over a GROUP of axes is not affine-invariant,
so physical units are the only space where the columns mean the same thing.
evalsets/ — per-goal eval sets, built from the 16-task SUBSET manifest
move_to_nav_fridge_v3.0 400 segments / 2 tasks / 290,892 frames
move_to_nav_floors_v3.0 896 segments / 4 tasks / 387,485 frames
meta/ and data/ only. Video is symlinked into the H200's nav-subset tree, so relink against
your own download: ln -s <2026-challenge-demos>/videos <dataset>/videos. The video pointers
in meta/episodes are the original release's chunk/file/timestamp values. depth features are
already dropped — only RGB was fetched on that box.
floors is the strongest cross-task pooling condition available in the subset: the same goal
in scrubbing_bathroom_floor, sorting_bottles_cans_and_paper, unloading_the_car and
vacuuming_floors.
- Downloads last month
- 54