Datasets:
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 "tsfile/tsfile_py_cpp.pyx", line 567, in tsfile.tsfile_py_cpp.tsfile_reader_new_c
tsfile.exceptions.FileOpenError: 28:
The above exception was the direct cause of the following exception:
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/tsfile/tsfile.py", line 271, in _split_generators
scan = self._scan_metadata(all_files)
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/tsfile/tsfile.py", line 318, in _scan_metadata
with self._open_reader(file) as reader:
~~~~~~~~~~~~~~~~~^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/tsfile/tsfile.py", line 742, in _open_reader
return TsFileReader(file)
File "tsfile/tsfile_reader.pyx", line 323, in tsfile.tsfile_reader.TsFileReaderPy.__init__
SystemError: <class '_weakrefset.WeakSet'> returned a result with an exception set
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.
First Thread GR00T TsFile
This dataset is an Apache TsFile conversion of
120ft/first-thread-gr00t, a LeRobot v2.1 / GR00T Unitree G1-D teleoperation
dataset for the task "thread lamp part".
The converted repository contains time-series and tabular numeric robot data. The three camera streams remain in the original Hugging Face dataset and are not duplicated here.
Source Dataset and Provenance
- Original dataset:
120ft/first-thread-gr00t - Pinned source revision:
b8a57a601ac099cec83fe0e49589e1032f2d197c - Publisher/original organization: 120ft Factory AB (
120ft) - Repository and video contributor:
chrisvtom - License: not declared by the source dataset card
- Paper/citation: not provided by the source dataset card
- Robot type:
g1d - LeRobot codebase version:
v2.1 - Task:
thread lamp part(task_index=0) - Split:
train - Sampling rate: 30 fps
- Scale: 72 episodes, 96,960 frames, 1 task
- Source Parquet layout:
data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet - Source Parquet shards: 72
The source card states that the v2.1 GR00T form was converted from a v3.0 dataset in the 120ft data-collection repository. This conversion uses the pinned published LeRobot v2.1 Parquet files as its authoritative numeric input.
Converted Files
- TsFile:
data/120ft_first_thread_gr00t_train.tsfile - Table:
120ft_first_thread_gr00t_train - Rows: 96,960
- Episodes/devices: 72
- Columns: 37 total (1 TIME, 2 TAG, 34 FIELD)
- TsFile size: 6.30 MiB
- Time precision: milliseconds
- Metadata: source
meta/files are preserved;meta/info.jsonis rewritten to describe the TsFile schema, mapping, provenance, and video policy.
TsFile Schema
Time is an INT64 millisecond timestamp computed as
round(timestamp * 1000). It restarts at zero in each episode.
| Role | Columns | TsFile type |
|---|---|---|
| TIME | Time |
INT64/TIMESTAMP |
| TAG | episode_index, task_index |
STRING device tags |
| FIELD | frame_index, sample_index |
INT64 |
| FIELD | observation_state_0 ... observation_state_15 |
FLOAT |
| FIELD | action_0 ... action_15 |
FLOAT |
The 16 state/action dimensions retain the ordering documented in source
meta/info.json: seven left-arm joints, seven right-arm joints, then left and
right Dex1 gripper values.
Conversion Notes
- All 72 source episode Parquet files are merged into one train table-model
TsFile. Filter by
episode_indexandtask_indexto select a trajectory. observation.state[16]andaction[16]are flattened to scalar FLOAT fields. Source prefixes are preserved and.is replaced with_.- Source
timestampis dropped after Time synthesis because it is exactly represented byTime / 1000seconds at millisecond precision. - Source
indexis retained assample_index;frame_indexis unchanged. - No source rows, episodes, tasks, or numeric vector dimensions are dropped.
Encoding and Compression
The conversion generated and fully validated both permitted numeric profiles,
then selected the smaller valid result (zstd):
Time:TS_2DIFF + LZ4- FLOAT/DOUBLE FIELD values:
GORILLA + ZSTD - INT32/INT64 FIELD values:
TS_2DIFF + ZSTD - BOOLEAN FIELD values:
RLE + LZ4 - TAG values: TsFile table device/TAG mechanism (
PLAIN + LZ4storage)
The final TsFile is 0.5578 times the combined size of the 72 source Parquet files.
Videos
Videos are not included in this converted repository. The pinned source has 216 frame-aligned H.264 480x640 MP4 files at 30 fps, split across three streams:
observation.images.head- 72 per-episode MP4 filesobservation.images.left_wrist- 72 per-episode MP4 filesobservation.images.right_wrist- 72 per-episode MP4 files
Source template: videos/chunk-{episode_chunk:03d}/{video_key}/episode_{episode_index:06d}.mp4. Numeric rows remain aligned
with the original videos through episode_index, frame_index, and source
episode metadata.
Validation
Local validation checks source and staged row counts, unique
(episode_index, task_index, Time) keys, per-episode monotonic Time, table/TAG
schema, full Java query readback, SHA-256, and actual per-column encodings and
compression. Conversion scripts and validation reports are intentionally not
part of the upload-ready dataset.
Minimal Read Example
from tsfile import TsFileReader
reader = TsFileReader("data/120ft_first_thread_gr00t_train.tsfile")
table_name = "120ft_first_thread_gr00t_train"
columns = [
"episode_index",
"task_index",
"frame_index",
"sample_index",
"observation_state_0",
"action_0",
]
with reader.query_table(table_name, columns, batch_size=65536) as result:
batch = result.read_arrow_batch()
print(batch.to_pandas().head())
reader.close()
Citation
The source dataset does not provide a paper or completed citation. Cite the original Hugging Face dataset, 120ft Factory AB, and the pinned source revision when using this converted artifact.
- Downloads last month
- -