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Datasets:
l2aggle
/
Agibot2UnitreeG1Retarget

Tasks:
Robotics
ArXiv:
Tags:
motion-retargeting
humanoid-robot
agibot
unitree-g1
License:
Dataset card Files
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The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
jsonl: binary
__key__: string
__url__: string
mp4: null
to
{'mp4': Value('binary'), '__key__': Value('string'), '__url__': Value('string')}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
                  return get_rows(
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/utils.py", line 77, in get_rows
                  rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2361, in __iter__
                  for key, example in ex_iterable:
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1882, in __iter__
                  for key, pa_table in self._iter_arrow():
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1914, in _iter_arrow
                  pa_table = cast_table_to_features(pa_table, self.features)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2192, in cast_table_to_features
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              jsonl: binary
              __key__: string
              __url__: string
              mp4: null
              to
              {'mp4': Value('binary'), '__key__': Value('string'), '__url__': Value('string')}
              because column names don't match

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Agibot2UnitreeG1Retarget Dataset

Paper | Project Page | Code

Description

This dataset contains action retargeting data from Agibot to UnitreeG1 humanoid robot.

Dataset Size

  • Total size: ~30GB
  • Split into 7 parts (A2UG1_dataset.tar.gz.aa to A2UG1_dataset.tar.gz.ag)
  • Each part is approximately 4GB

Usage

Method 1: Using Hugging Face Hub (Recommended) 

pip install huggingface-hub

from huggingface_hub import snapshot_download

# Download the entire dataset
snapshot_download(
    repo_id="l2aggle/Agibot2UnitreeG1Retarget",
    repo_type="dataset",
    local_dir="./Agibot2UnitreeG1Retarget"
)

Method 2: Using Git with LFS 

# Make sure git-lfs is installed
git lfs install

# Clone the repository (this will download LFS pointer files)
git clone https://huggingface.co/datasets/l2aggle/Agibot2UnitreeG1Retarget
cd Agibot2UnitreeG1Retarget

# Download the actual large files
git lfs pull

Method 3: Manual Download

Download individual parts through the Hugging Face web interface: https://huggingface.co/datasets/l2aggle/Agibot2UnitreeG1Retarget/tree/main

Extract Dataset

After downloading, extract the complete dataset:

# Combine and extract all parts
cat A2UG1_dataset.tar.gz.* | tar -xzf -

This will create the complete A2UG1_dataset folder with all original files.

File Structure 

A2UG1_dataset/
├── [your dataset structure will be shown here after extraction]

Requirements

  • At least 60GB free disk space (30GB for download + 30GB for extraction)
  • For Method 1: Python 3.6+ with huggingface-hub package
  • For Method 2: Git with Git LFS support
  • tar utility (standard on Linux/Mac, available on Windows via WSL or Git Bash)

Installation Requirements 

# For Method 1
pip install huggingface-hub

# For Method 2 (if git-lfs not installed)
# Ubuntu/Debian:
sudo apt install git-lfs
# macOS:
brew install git-lfs
# Windows: download from https://git-lfs.github.io/

License

Apache 2.0

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Paper for l2aggle/Agibot2UnitreeG1Retarget