datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
dead-internet-observatoryTextBraTS
TextBraTS
A volume-level text-image public dataset with novel text-guided 3D brain tumor segmentation from BraTS challenge.
Paper
Introduction
TextBraTS is an open-access dataset designed to advance research in text-guided 3D brain tumor segmentation. It includes paired multi-modal brain MRI scans and expertly annotated radiology reports, enabling the development and evaluation of multi-modal deep learning models that bridge vision and language in neuro-oncology. Our… See the full description on the dataset page: https://huggingface.co/datasets/Jupitern52/TextBraTS.fineweb_2_500k_both_deduplicatedjupiter-tasktrove-dapo-artifacts
Jupiter TaskTrove DAPO — campaign artifacts
Standalone artifact archive for the jupiter-tasktrove-dapo campaign: a six-arm
objective ablation (GRPO control vs DAPO variants vs GSPO) training
Qwen/Qwen3-Coder-30B-A3B-Instruct with agentic RL (MarinSkyRL / SkyRL fully-async GRPO
trainers, Harbor + Daytona sandboxed terminus-2 rollouts) on competitive-programming
tasks, run on JSC Jupiter (GH200) 2026-08-20 → 2026-08-31.
The campaign closed inconclusive (platform degradation, a… See the full description on the dataset page: https://huggingface.co/datasets/penfever/jupiter-tasktrove-dapo-artifacts.albedoe1_gpt_long_swegym_sandboxes_4x_glm_4.7_traces_jupiterharbor-devel-sandboxes_glm_4.7_traces_jupiterFRED
Flooded Road Environments Dataset (FRED)
This autonomous vehicle dataset has been developed to enable research into the detection of flooded roads during on-road deployment. The dataset was collected using a Renault Zoe with custom modifications to enable autonomy, including front and rear Blackfly cameras, an Ouster OS1 LiDAR, and a GNSS-corrected IMU. Data has been collected using the vehicle's sensor stack from 5 separate locations around Brisbane, Australia, both during and… See the full description on the dataset page: https://huggingface.co/datasets/CMalone-Jupiter/FRED.terminal_bench_2_dev_set_part1_10k_glm_4_7_traces_jupiter_20260226_182808e1_weighted_issue_50k_sandboxes_glm_4.7_traces_jupiterexp-psu-swesmith-31K_glm_4.7_traces_jupitere1_gpt_long_r2egym_sandboxes_4x_glm_4.7_traces_jupiterneulab-nebius-swe-agent-trajectories-sandboxes_glm_4.7_traces_jupitere1_gpt_long_scaffold_sandboxes_4x_glm_4.7_traces_jupitere1_weighted_superuser_50k_sandboxes_glm_4.7_traces_jupiterexp-syh-r2egym-askllm-constrained_glm_4.7_traces_jupiterlm-eval-results-Kukedlc-Jupiter-k-7B-slerp-private
Dataset Card for Evaluation run of Kukedlc/Jupiter-k-7B-slerp
Dataset automatically created during the evaluation run of model Kukedlc/Jupiter-k-7B-slerp
The dataset is composed of 62 configuration(s), each one corresponding to one of the evaluated task.
The dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results.
An… See the full description on the dataset page: https://huggingface.co/datasets/nyu-dice-lab/lm-eval-results-Kukedlc-Jupiter-k-7B-slerp-private.inferredbugs-sandboxes_glm_4.7_traces_jupiterswegym-tasks-patched-upsampled_10k_glm_4.7_traces_jupiterexp-uns-r2egym-2_1x_glm_4.7_traces_jupiterexp_rle_detailed_10k_glm_4.7_traces_jupiterexp_rpt_stack-bash-withtests-gpt5mini_glm_4.7_traces_jupiterexp_flat25_pseudocode_10k_glm_4.7_traces_jupitere1_weighted_swesmith_50k_sandboxes_glm_4.7_traces_jupitere1_gpt_long_tor_sandboxes_4x_glm_4.7_traces_jupiterexp-uns-r2egym-16_8x_glm_4.7_traces_jupiterneulab-nnetnav-live-sandboxes_glm_4.7_traces_jupitere1_embedding_d1_constrain_sandboxes_glm_4.7_traces_jupiterterminal_bench_2_exp_gfi_swesmith_random_filtered_10K_glm_4_7_traces_jupiter_20e2c1924fgithub-dockerfiles-docker-exp-taskmaster2-tasks_glm_4.7_traces_jupiter