datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
astro-classification-redshifts
AstroClassification and Redshifts Datasets
This dataset was used for the AstroClassification and Redshifts introduced in Connect Later: Improving Fine-tuning for Robustness with Targeted Augmentations. This is a dataset of simulated astronomical time-series (e.g., supernovae, active galactic nuclei), and the task is to classify the object type (AstroClassification) or predict the object's redshift (Redshifts).
Repository: https://github.com/helenqu/connect-later
Paper: will be… See the full description on the dataset page: https://huggingface.co/datasets/helenqu/astro-classification-redshifts.slop-classification
Slop classifier dataset
A human-annotated dataset for studying and classifying AI-generated text that people perceive as “AI slop.”
The dataset is built from samples collected from existing public datasets and annotated through the Bench Labs SlopFinder interface.
Slop score
Each sample receives a score based on human votes:
-1 = definitely slop
0 = undecided / neutral
+1 = not slop at all
The score represents human judgment, not an objective measure of quality… See the full description on the dataset page: https://huggingface.co/datasets/bench-labs/slop-classification.Wikipedia_RAG_QA_Classification
🏛️ Wikipedia RAG QA Dataset for Retrieval-Augmented Generation Training
📊 Dataset Description
This dataset contains 300,000+ validated model-generated responses to Wikipedia content, specifically designed for Retrieval-Augmented Generation (RAG) applications and SQL database insertion tasks. Generated by Jeeney AI Reloaded 207M GPT with specialized RAG tuning.
🖥️ Demo Interface: Discord
Live Chat Demo on Discord: https://discord.gg/Xe9tHFCS9h
The full CJ… See the full description on the dataset page: https://huggingface.co/datasets/CJJones/Wikipedia_RAG_QA_Classification.skill-level-classification-datasettext-classification-comparison
Text Classification Comparison: Supervised vs Unsupervised on stanfordnlp/imdb
Dataset
stanfordnlp/imdb (Maas et al., 2011)
50,000 IMDB movie reviews: 25,000 train / 25,000 test
Binary sentiment: 0 (negative) / 1 (positive), perfectly balanced in both splits
Preprocessing: TF-IDF (15,000 features, bigrams, sublinear TF, min_df=3)
Models Chosen
Model
Type
Key Reference
Why
Logistic Regression
Linear supervised
McFadden (1974); Ng &… See the full description on the dataset page: https://huggingface.co/datasets/IntimateUser6969/text-classification-comparison.Quran_Classificationer_v2_flat_classificationleaderboard-data-classification