LIBERO: Benchmarking Knowledge Transfer for Lifelong Robot Learning
Paper • 2306.03310 • Published • 3
Dataset Viewer
The dataset viewer is not available for this subset.
Cannot get the split names for the config 'default' of the dataset.
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 68, 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.
FT-LLM-2026-RAMEN LIBERO TsFile
This repository is the Apache TsFile edition of
FT-LLM-2026-RAMEN/libero, a LeRobot v3.0 Panda manipulation dataset based on
the LIBERO benchmark. It contains numeric robot state, actions, frame timing,
episode/task dimensions, and the source meta/ records.
Source and attribution
- Source dataset:
FT-LLM-2026-RAMEN/libero - Source organization: FT-LLM-2026-RAMEN
- Repository contributor: yusei926; the public history credits this account with the LeRobot v3.0 layout and Japanese task-description update
- Benchmark: LIBERO: Benchmarking Knowledge Transfer for Lifelong Robot Learning
- LIBERO authors: Bo Liu, Yifeng Zhu, Chongkai Gao, Yihao Feng, Qiang Liu, Yuke Zhu, Peter Stone
- License: the source repository does not state a license, so none is inferred here
Scale and layout
- Split:
train - Episodes: 1,693
- Frame rows: 273,465
- Task indexes: 40
- Sampling rate: 10 Hz
- Source numeric layout: 377 Parquet shards, 20,264,464 bytes
- TsFile layout: one
data/ft_llm_2026_ramen_libero.tsfiletable containing all episodes, 16,128,325 bytes - Table name:
ft_llm_2026_ramen_libero
The source meta/tasks.parquet assigns the same general Japanese robot-task
sentence to all 40 task indexes. The indexes are retained without inventing
more specific task labels.
TsFile schema
| Role | Columns | Type and meaning |
|---|---|---|
| TIME | Time |
INT64 milliseconds, round(timestamp * 1000) |
| TAG | episode_index, task_index |
Original LeRobot episode and task dimensions |
| FIELD | frame_index, sample_index |
Original frame index and source index |
| FIELD | observation_state_0 ... observation_state_7 |
Eight FLOAT Panda state values |
| FIELD | action_0 ... action_6 |
Seven FLOAT action values |
Rows are ordered by episode_index, task_index, and Time. Time starts at
0 for every episode and advances by 100 ms at 10 Hz. Source timestamp is not
stored separately because it is exactly recoverable as Time / 1000. Source
index is named sample_index; frame_index is retained unchanged.
Videos
Videos are not included here. The original repository contains 3,386 MP4 files, 1,693 for each 256 x 256 AV1 stream:
The source video path is
videos/{video_key}/chunk-{chunk_index:03d}/file-{file_index:03d}.mp4. Use episode_index and frame_index together
with meta/episodes/chunk-000/file-000.parquet to align TsFile rows to video
frames. Hugging Face reports the original videos/ tree as 1.92 GB.
Read example
from tsfile import TsFileReader
reader = TsFileReader("data/ft_llm_2026_ramen_libero.tsfile")
table_name = "ft_llm_2026_ramen_libero"
print(reader.get_all_table_schemas()[table_name])
with reader.query_table(
table_name,
["episode_index", "task_index", "frame_index", "action_0", "observation_state_0"],
batch_size=65536,
) as result:
print(result.read_arrow_batch().to_pandas().head())
reader.close()
Citation
@inproceedings{liu2023libero,
title={LIBERO: Benchmarking Knowledge Transfer for Lifelong Robot Learning},
author={Liu, Bo and Zhu, Yifeng and Gao, Chongkai and Feng, Yihao and Liu, Qiang and Zhu, Yuke and Stone, Peter},
booktitle={Advances in Neural Information Processing Systems},
year={2023}
}
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