datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
acrft-annot-noprop
acrft-annot-noprop
RLT annotation for AC-RFT critic training: raw memmaps (.dat) + meta.json, read directly by
scripts/train_rlt_critic.py and scripts/eval_rlt_critic.py in the openpi fork.
Shapes are in meta.json: rl_token [T, D], base_action [T, N, H, A], action_chunk [T, H, A],
reward/mc_return/done/episode_index/frame_index [T], base_action_heldout [T, num_heldout, H, A].
dtype and reward_scheme are in meta.json. Load with numpy.memmap.
from huggingface_hub import… See the full description on the dataset page: https://huggingface.co/datasets/jellyho/acrft-annot-noprop.Acrobot-v1
Acrobot-v1 - Imitation Learning Datasets
This is a dataset created by Imitation Learning Datasets project.
It was created by using Stable Baselines weights from a DQN policy from HuggingFace.
Description
The dataset consists of 1,000 episodes with an average episodic reward of -69.852.
Each entry consists of:
obs (list): observation with length 6.
action (int): action (0, 1 or 2).
reward (float): reward point for that timestep.
episode_returns (bool): if that state was… See the full description on the dataset page: https://huggingface.co/datasets/NathanGavenski/Acrobot-v1.repro-time-series-saliency-maps-explaining-models-across-multiple-domains-traces
Agent traces
Agent sessions published from a Trackio Logbook.
acr