datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
bioburden_labelled_datacommon_voice_16_1_hi_pseudo_labelledmls_it_pseudo_labelled-large-v3common_voice_17_0_en_pseudo_labelledcommon_voice_16_1_hi_pseudo_labellednurc-sp_pseudo_labelledvoxpopuli_en_pseudo_labelledCSSR-S_labelled_suicidewatch_posts_reddit
Evaluating Reasoning LLMs for Suicide Screening with the Columbia-Suicide Severity Rating Scale
Full code and supplementary materials are available at https://github.com/av9ash/llm_cssrs_code.
License and Citation
This project is released under the Creative Commons Attribution 4.0 International (CC BY 4.0) license.Any use or reuse of this work please cite the following:
@article{patil2025evaluating,
title={Evaluating Reasoning LLMs for Suicide Screening with the… See the full description on the dataset page: https://huggingface.co/datasets/av9ash/CSSR-S_labelled_suicidewatch_posts_reddit.mmlu-auxiliary-train-auto-labelled
Dataset Card for MMLU Auxiliary Trained Set Labelled by e5-mistral-7b-instruct
Dataset Description
Dataset Summary
This dataset, named "MMLU Auxiliary Trained Set Labelled by e5-mistral-7b-instruct," consists of 99,842 examples spanning various subjects. Each instance includes a question, multiple choice options, a subject category, and an answer. The unique aspect of this dataset is the task label for each question, generated by a zero-shot classifier… See the full description on the dataset page: https://huggingface.co/datasets/kz919/mmlu-auxiliary-train-auto-labelled.zeroth-kspon_pseudo_labelledtexts-labelled-grammaticalitycommon_voice_16_1_en_pseudo_labelledcommon_voice_17_0_es_pseudo_labelledr_judge_labelled
R-Judge with LLM-Judge Labels
This dataset augments the R-Judge benchmark with automated safety labels produced by an LLM judge. R-Judge is a benchmark for evaluating the safety judgment capability of LLMs in multi-turn agent scenarios, spanning five application domains.
Files
File
Description
r_judge_data.csv
Base dataset extracted from R-Judge (568 rows, deduplicated)
r_judge_labelled_anthropic_claude-sonnet-4-6.csv
Base dataset augmented with… See the full description on the dataset page: https://huggingface.co/datasets/Glide-py/r_judge_labelled.voxpopuli_es_pseudo_labelledgold_labelled_gensDataset of 12600 answer generations from a 1.4b fine-tuned Pythia policy model, using the AlpacaFarm dataset 'val' split, and labelled with the AlpacaFarm 'reward-model-human' to give 'gold' scores.
Used during best-of-n inference in 'Reward Model Ensembles Mitigate Overoptimization'
common_voice_16_1_fa_pseudo_labelledcommon_voice_16_AR_pseudo_labelledcommon_voice_17_0_pseudo_labelled-large-v3yelp_restaurant_review_labelled
Dataset Card for "yelp_restaurant_review_labelled"
More Information needed
More info about the dataset
dataset downloaded from Yelp
labelling
if review star < 3 is 0 (negative)else if review star == 3 is 1 (neutral)else if review star > 3 is 2 (positive)
common_voice_16_1_ko_pseudo_labelledcommon_voice_13_0_bg_pseudo_labelledcommon_voice_17_0_eu_pseudo_labelledcommon_voice_13_0_hi_pseudo_labelledMultilingual-USAS-Labelled-Silver-Wikipedia
Multilingual USAS Silver Labelled Wikipedia Articles
Silver-labelled Wikipedia article text for training USAS semantic taggers and Multi-Word
Expression (MWE) identifiers, covering 8 Wikipedia language sites. The source text comes from the
HuggingFace HuggingFaceFW/finewiki
dataset, restricted to articles rated Good (GA) or Featured (FA) — using the article ID list from
ucrelnlp/wikipedia-ga-fa-ids — and
then sentence split and automatically tagged with USAS semantic tags and… See the full description on the dataset page: https://huggingface.co/datasets/ucrelnlp/Multilingual-USAS-Labelled-Silver-Wikipedia.common_voice_17_0_pt_pseudo_labelled-large-v3trashify_manual_labelled_images
Load data
import datasets
dataset = datasets.load_dataset("mrdbourke/trashify_manual_labelled_images")
dataset
View a sample
dataset["train"][0]
Output:
{'image': <PIL.Image.Image image mode=RGB size=960x1280>,
'image_id': 292,
'annotations': {'file_name': ['00347467-13f1-4cb9-94aa-4e4369457e0c.jpeg',
'00347467-13f1-4cb9-94aa-4e4369457e0c.jpeg'],
'image_id': [292, 292],
'category_id': [1, 0],
'bbox': [[523.7000122070312,
545.0999755859375… See the full description on the dataset page: https://huggingface.co/datasets/mrdbourke/trashify_manual_labelled_images.common_voice_16_1_hi_pseudo_labelledcommon_voice_17_0_it_pseudo_labelled-large-v3common_voice_17_0_ar_pseudo_labelled-large-v3