datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
GeNTE_ita-evalThis dataset adapts the GeNTE dataset to be run on ItaEval.
In particular, we selected the five initial instances from the dataset and used them as few-shot examples ("train" split in this release).
Please check the original dataset for more details on GeNTE. If you use the dataset, please consider citing the paper:
@inproceedings{piergentili-etal-2023-hi,
title = "Hi Guys or Hi Folks? Benchmarking Gender-Neutral Machine Translation with the {G}e{NTE} Corpus",
author = "Piergentili… See the full description on the dataset page: https://huggingface.co/datasets/RiTA-nlp/GeNTE_ita-eval.UINAUILBRAVO
BRAVO Bench
This study introduces BRAVO (Building Regulation Answering & Visual Observation) Bench, the first benchmark designed to evaluate the capability of Multimodal Large Language Models (MLLMs) to perform compliance checking based on BIM-derived scenes. BRAVO Bench integrates 26 BIM-scenes, 59 textual normative provisions, and 5 regulatory illustrations, producing 1505 question–answer pairs across four diagnostic layers: scene perception, scene understanding, rule… See the full description on the dataset page: https://huggingface.co/datasets/ritanibar/BRAVO.20260504RL_testThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"robot_type": "so101_follower",
"total_episodes": 32,
"total_frames": 12528,
"total_tasks": 1,
"chunks_size": 1000,
"data_files_size_in_mb": 100,
"video_files_size_in_mb": 200,
"fps": 30,
"splits": {
"train": "0:32"
},
"data_path": "data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet",
"video_path":… See the full description on the dataset page: https://huggingface.co/datasets/RITAHuang/20260504RL_test.20260514_5ep_singlecamThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"robot_type": "so101_follower",
"total_episodes": 5,
"total_frames": 1855,
"total_tasks": 1,
"chunks_size": 1000,
"data_files_size_in_mb": 100,
"video_files_size_in_mb": 200,
"fps": 30,
"splits": {
"train": "0:5"
},
"data_path": "data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet",
"video_path":… See the full description on the dataset page: https://huggingface.co/datasets/RITAHuang/20260514_5ep_singlecam.20260513_25ep_singlecam_testThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"robot_type": "so101_follower",
"total_episodes": 25,
"total_frames": 9231,
"total_tasks": 1,
"chunks_size": 1000,
"data_files_size_in_mb": 100,
"video_files_size_in_mb": 200,
"fps": 30,
"splits": {
"train": "0:25"
},
"data_path": "data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet",
"video_path":… See the full description on the dataset page: https://huggingface.co/datasets/RITAHuang/20260513_25ep_singlecam_test.ami_2020
Dataset Card for Dataset Name
The Automatic Misogyny Identification was part of the 7th evaluation campaign EVALITA 2020. Please refer to the official website for more details.
Data is also available on the ELG website.
Data is released under the CC-BY NC SA 4.0
The rest of the dataset card is WIP :)
Dataset Details
Dataset Description
Curated by: [More Information Needed]
Funded by [optional]: [More Information Needed]
Shared by [optional]:… See the full description on the dataset page: https://huggingface.co/datasets/RiTA-nlp/ami_2020.5.8_act_test2_from_sent_action_hamer_aligned_v25.24_merged50_bana_from_sent_actionitaeval-results
Dataset Card for Evaluation run of CohereForAI/aya-expanse-8b
Dataset automatically created during the evaluation run of model CohereForAI/aya-expanse-8b
The dataset is composed of 330 configuration(s), each one corresponding to one of the evaluated task.
The dataset has been created from 58 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/RiTA-nlp/itaeval-results.