Dataset Viewer
The dataset viewer is not available for this split.
Cannot extract the features (columns) for the split 'train' of the config 'default' of the dataset.
Error code: FeaturesError
Exception: ArrowInvalid
Message: Schema at index 1 was different:
4000: struct<partnet_mobility_id: int64, scale: double>
4001: struct<partnet_mobility_id: int64, scale: double>
4003: struct<partnet_mobility_id: int64, scale: double>
4006: struct<partnet_mobility_id: int64, scale: double>
4008: struct<partnet_mobility_id: int64, scale: double>
4009: struct<partnet_mobility_id: int64, scale: double>
4010: struct<partnet_mobility_id: int64, scale: double>
4011: struct<partnet_mobility_id: int64, scale: double>
4012: struct<partnet_mobility_id: int64, scale: double>
4016: struct<partnet_mobility_id: int64, scale: double>
4017: struct<partnet_mobility_id: int64, scale: double>
4018: struct<partnet_mobility_id: int64, scale: double>
4019: struct<partnet_mobility_id: int64, scale: double>
4020: struct<partnet_mobility_id: int64, scale: double>
4021: struct<partnet_mobility_id: int64, scale: double>
4022: struct<partnet_mobility_id: int64, scale: double>
4023: struct<partnet_mobility_id: int64, scale: double>
4024: struct<partnet_mobility_id: int64, scale: double>
4025: struct<partnet_mobility_id: int64, scale: double>
4031: struct<partnet_mobility_id: int64, scale: double>
4032: struct<partnet_mobility_id: int64, scale: double>
4035: struct<partnet_mobility_id: int64, scale: double>
4043: struct<partnet_mobility_id: int64, scale: double>
4044: struct<partnet_mobility_id: int64, scale: double>
4045: struct<partnet_mobility_id: int64, scale: double>
4051: struct<partnet_mobility_id: int64, scale: double>
4052: struct<partnet_mobility_id: int64, scale: double>
4055: struct<partnet_mobility_id: int64, scale: double>
4056: struct<partnet_mobility_id: int64, scale: double>
vs
1000: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1001: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1002: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1006: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1007: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1014: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1017: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1018: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1025: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1026: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1027: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1028: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1030: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1031: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1034: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1036: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1038: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1039: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1041: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1042: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1044: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1045: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1046: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1047: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1049: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1051: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1052: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1054: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1057: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1060: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1061: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1062: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1063: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1064: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1065: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1067: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1068: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1073: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1075: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1077: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1078: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1081: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
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 3422, 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 2187, 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 2391, in iter
for key, example in iterator:
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 1904, 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 527, in _iter_arrow
yield new_key, pa.Table.from_batches(chunks_buffer)
File "pyarrow/table.pxi", line 4116, in pyarrow.lib.Table.from_batches
File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status
File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status
pyarrow.lib.ArrowInvalid: Schema at index 1 was different:
4000: struct<partnet_mobility_id: int64, scale: double>
4001: struct<partnet_mobility_id: int64, scale: double>
4003: struct<partnet_mobility_id: int64, scale: double>
4006: struct<partnet_mobility_id: int64, scale: double>
4008: struct<partnet_mobility_id: int64, scale: double>
4009: struct<partnet_mobility_id: int64, scale: double>
4010: struct<partnet_mobility_id: int64, scale: double>
4011: struct<partnet_mobility_id: int64, scale: double>
4012: struct<partnet_mobility_id: int64, scale: double>
4016: struct<partnet_mobility_id: int64, scale: double>
4017: struct<partnet_mobility_id: int64, scale: double>
4018: struct<partnet_mobility_id: int64, scale: double>
4019: struct<partnet_mobility_id: int64, scale: double>
4020: struct<partnet_mobility_id: int64, scale: double>
4021: struct<partnet_mobility_id: int64, scale: double>
4022: struct<partnet_mobility_id: int64, scale: double>
4023: struct<partnet_mobility_id: int64, scale: double>
4024: struct<partnet_mobility_id: int64, scale: double>
4025: struct<partnet_mobility_id: int64, scale: double>
4031: struct<partnet_mobility_id: int64, scale: double>
4032: struct<partnet_mobility_id: int64, scale: double>
4035: struct<partnet_mobility_id: int64, scale: double>
4043: struct<partnet_mobility_id: int64, scale: double>
4044: struct<partnet_mobility_id: int64, scale: double>
4045: struct<partnet_mobility_id: int64, scale: double>
4051: struct<partnet_mobility_id: int64, scale: double>
4052: struct<partnet_mobility_id: int64, scale: double>
4055: struct<partnet_mobility_id: int64, scale: double>
4056: struct<partnet_mobility_id: int64, scale: double>
vs
1000: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1001: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1002: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1006: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1007: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1014: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1017: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1018: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1025: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1026: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1027: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1028: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1030: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1031: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1034: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1036: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1038: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1039: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1041: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1042: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1044: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1045: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1046: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1047: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1049: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1051: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1052: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1054: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1057: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1060: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1061: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1062: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1063: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1064: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1065: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1067: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1068: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1073: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1075: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1077: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1078: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1081: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>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.
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empty or missing yaml metadata in repo card
(https://huggingface.co/docs/hub/datasets-cards)
RLinf: Reinforcement Learning Infrastructure for Agentic AI
RLinf is a flexible and scalable open-source infrastructure designed for post-training foundation models (LLMs, VLMs, VLAs) via reinforcement learning. The 'inf' in RLinf stands for Infrastructure, highlighting its role as a robust backbone for next-generation training. It also stands for Infinite, symbolizing the system’s support for open-ended learning, continuous generalization, and limitless possibilities in intelligence development.
RLinf Assets for ManiSkill
Thanks to the assets from objaverse, our assets are built upon their work. To validate the effectiveness of our training–inference framework RLinf, we adapt methods from rl4vla into our RLinf framework.
How to Use
Users can download the assets required for ManiSkill tasks in our framework and place them onto the target development machine:
- The
assets/folder should be placed in:/pathtorepo/rlinf/envs/maniskill/assets/ - The
.sapien/folder should be placed in:~/.sapien/ - The
.maniskill/folder should be placed in:~/.maniskill/
License
We follow the license of Objaverse-XL. The use of the dataset as a whole is licensed under the ODC-By v1.0 license. Individual objects in Objaverse-XL are licensed under different licenses.
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