The dataset viewer is not available for this split.
Error code: FeaturesError
Exception: ValueError
Message: Failed to convert pandas DataFrame to Arrow Table from file hf://datasets/Ryhn98/StyleDrive-Dataset@c575009715199a1234245b248667ad987cc60e84/styletest.json.
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 228, in compute_first_rows_from_streaming_response
iterable_dataset = iterable_dataset._resolve_features()
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 3357, in _resolve_features
features = _infer_features_from_batch(self.with_format(None)._head())
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2111, in _head
return next(iter(self.iter(batch_size=n)))
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2315, in iter
for key, example in iterator:
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1856, 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 1878, in _iter_arrow
yield from self.ex_iterable._iter_arrow()
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 476, in _iter_arrow
for key, pa_table in iterator:
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 323, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 172, in _generate_tables
raise ValueError(
ValueError: Failed to convert pandas DataFrame to Arrow Table from file hf://datasets/Ryhn98/StyleDrive-Dataset@c575009715199a1234245b248667ad987cc60e84/styletest.json.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.
We release the checkpoints and StyleDrive's preference annotations in this huggingface repo.
StyleDrive is the first large-scale real-world dataset designed to advance personalized end-to-end autonomous driving (E2EAD).
This repository includes:
🧠 Model checkpoints.
📊 StyleDrive datasets' annotations.
These resources support training and evaluating models under our proposed benchmark for personalized E2EAD, enabling more human-aligned and context-aware driving behaviors.
For env configs, code, training pipelines, and benchmark details, please visit our GitHub repository and Paper.
If you find StyleDrive is useful in your research or applications, please consider giving us a star 🌟 on GitHub and citing it by the following BibTeX entry:
@article{hao2025styledrive,
title={StyleDrive: Towards Driving-Style Aware Benchmarking of End-To-End Autonomous Driving},
author={Hao, Ruiyang and Jing, Bowen and Yu, Haibao and Nie, Zaiqing},
journal={arXiv preprint arXiv:2506.23982},
year={2025}
}
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