datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
gsworld_pour_mustard_sft_100
GSWorld FR3 PourMustard SFT 100
LeRobot v2.1 dataset converted from GSWorld / ManiSkill motion-planning demonstrations.
Task: pour the mustard bottle onto the bread slice
Robot: fr3_umi
Episodes: 100
Frames: 22041
FPS: 20
Schema: GSWorld dual-camera, DROID-style OpenPI fields
Cameras: exterior_image_1_left from GSWorld right_cam, wrist_image_left from GSWorld wrist_cam
State: 7 arm joint positions + 1 gripper position
Action: 8D FR3 UMI env-native pd_joint_pos
OpenPI reproduction… See the full description on the dataset page: https://huggingface.co/datasets/gst0312/gsworld_pour_mustard_sft_100.pythia-1.4B-tldr-iter-1pythia-1.4B-tldr-vllm-quad-iter-1pythia-1.4B-tldrpythia-1.4B-tldr-iter-2pythia-1.4B-tldr-local-iter-2pythia-1.4B-tldr-vllm-pair-iter-3pythia-1.4B-tldr-iter1pythia-1.4B-tldr-ws-iter-1pythia-1.4B-tldr-vllm-iter-1pythia-1.4B-tldr-dpo-pair-iter-1pythia-1.4B-tldr-two-words-iter-1pythia-1.4B-tldr-two-words-gpt-4o-iter-1pythia-1.4B-tldr-vllm-pair-iter-1pythia-1.4B-tldr-spin-iter-1pythia-1.4B-tldr-iter-0pythia-1.4B-tldr-vllm-pair-iter-2pythia-1.4B-tldr-local-iter-1gswlc-galaxy-properties
GSWLC-2 Galaxy Properties
Part of the Astronomy Datasets collection on Hugging Face.
659,229 galaxies with physical properties derived from UV-to-infrared spectral energy distribution (SED) fitting. GSWLC-2 (GALEX-SDSS-WISE Legacy Catalog 2) combines ultraviolet photometry from GALEX, optical photometry from SDSS, and mid-infrared photometry from WISE to estimate stellar masses, star formation rates, and dust attenuation for galaxies at redshifts 0.01 < z < 0.30.
Dataset… See the full description on the dataset page: https://huggingface.co/datasets/juliensimon/gswlc-galaxy-properties.pythia-1.4B-tldr-two-words-gpt-4o-reference-trainplot_holesgsw-eval
gsw-eval — Swiss-German evaluation benchmark
A small, honest benchmark over held-out text from
mischeiwiller/swiss-german-text.
Built by scripts/build_eval_split.py (task 6.1) via the pure mundart.eval layer.
Why not regional dialect-ID? Every row of the source corpus carries
region="unknown" — no greenlit source supplies a defensible dialect-region
label — so a regional classification task would require inventing labels we
cannot defend. The task the data genuinely supports is… See the full description on the dataset page: https://huggingface.co/datasets/mischeiwiller/gsw-eval.pythia-1.4B-tldr-two-words-gpt-4o-reference-valpythia-1.4B-tldr-gpt-pair-iter-1pythia-1.4B-tldr-gpt-val2GSWDirectionalSoundset
GSWDirectionalSoundset
tags: machine learning, gunshot sound, direction
Note: This is an AI-generated dataset so its content may be inaccurate or false
Dataset Description:
The 'GSWDirectionalSoundset' is a hypothetical dataset tailored for machine learning models that aim to analyze gunshot sounds to determine their direction. This dataset consists of audio clips from various shooting incidents captured by an array of strategically placed microphones. Each audio clip is annotated… See the full description on the dataset page: https://huggingface.co/datasets/infinite-dataset-hub/GSWDirectionalSoundset.rag_relevant_datarag_relevant_data_v5gsworld_stack_sft_100
GSWorld FR3 Stack SFT 100
LeRobot v2.1 dataset converted from GSWorld / ManiSkill motion-planning demonstrations.
Task: stack the red tomato can on top of the tomato soup can
Robot: fr3_umi
Episodes: 100
Frames: 16699
FPS: 20
Schema: GSWorld dual-camera, DROID-style OpenPI fields
Cameras: exterior_image_1_left from GSWorld right_cam, wrist_image_left from GSWorld wrist_cam
State: 7 arm joint positions + 1 gripper position
Action: 8D FR3 UMI env-native pd_joint_pos
OpenPI… See the full description on the dataset page: https://huggingface.co/datasets/gst0312/gsworld_stack_sft_100.pythia-1.4B-tldr-temp