datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
GenAI-EdSent
📄 Associated Paper
Title: Unveiling User Perceptions in the Generative AI Era: A Sentiment-Driven Evaluation of AI Educational Apps' Role in Digital Transformation of E-Teaching
Authors: Adeleh Mazaheriyan (Islamic Azad University) & Erfan Nourbakhsh (University of Isfahan)
Abstract: This study performs a sentiment-driven evaluation of user reviews from 22 top AI ed-apps on the Google Play Store to assess efficacy, challenges, and pedagogical implications. Our pipeline leverages… See the full description on the dataset page: https://huggingface.co/datasets/Erfan-Nourbakhsh/GenAI-EdSent.aime-gen-sft-v1
AIME-Style Problem Generation — SFT Dataset (v3)
Supervised fine-tuning data for teaching a small open model to author novel, valid,
difficulty-calibrated AIME-style competition problems — the behavior the companion
model is trained on.
Thesis: models fail at problem-posing for a diversity reason, not a reasoning reason. The
fix is data — distill an expensive search-and-filter pipeline into a cheap one-shot model. The
dataset is the deliverable; the model is the dataset made… See the full description on the dataset page: https://huggingface.co/datasets/William2390401/aime-gen-sft-v1.text-gen
Kroh:
Tonas dataset_kel.txt.
Tas tehst kroh:
Tehst→, ant tehst nymer la.\nTehst ala ton.
genaihub-dataset
Dataset Card for genaihub-dataset
This dataset has been created with distilabel.
Dataset Summary
This dataset contains a pipeline.yaml which can be used to reproduce the pipeline that generated it in distilabel using the distilabel CLI:
distilabel pipeline run --config "https://huggingface.co/datasets/allurisravanth/genaihub-dataset/raw/main/pipeline.yaml"
or explore the configuration:
distilabel pipeline info --config… See the full description on the dataset page: https://huggingface.co/datasets/allurisravanth/genaihub-dataset.