datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Home-Assistant-Requests-V2
Home Assistant Requests V2 Dataset
This dataset contains a list of requests and responses for a user interacting with a personal assistant that controls an instance of Home Assistant.
The updated V2 of the dataset is now multilingual, containing data in English, German, French, Spanish, and Polish. The dataset also contains multiple "personalities" for the assistant to respond in, such as a formal assistant, a sarcastic assistant, and a friendly assistant. Lastly, the dataset has… See the full description on the dataset page: https://huggingface.co/datasets/Vitinf/Home-Assistant-Requests-V2.GraphCode-Bench-500-v0
GraphCode-Bench-500-v0
GraphCode-Bench is a benchmark for evaluating LLMs on call-graph reasoning — given a function in a real-world repository, can a model identify which functions call it (upstream) or which functions it calls (downstream), across 1 and 2 hops?
Models are evaluated agentically: they receive read-only filesystem tools (list_directory, read_file, search_in_file) and up to 10 turns to explore the codebase before producing an answer.
Dataset summary… See the full description on the dataset page: https://huggingface.co/datasets/VittorioRossi/GraphCode-Bench-500-v0.wikipedia-id-qna
Wikipedia ID Synthetic QnA
This dataset contains synthetic question-answer pairs (QnA) generated using DeepSeek from Indonesian Wikipedia articles. The data has been sourced from this Wikipedia dataset, which contains a subset of Indonesian Wikipedia articles. Each entry includes a context, a related question and answer pair, and an unrelated question.
Dataset Structure
The dataset contains the following columns:
id: A unique identifier for each row.
context: A… See the full description on the dataset page: https://huggingface.co/datasets/vitoghif/wikipedia-id-qna.ViTaB-A
ViTaB-A Dataset
A normalized table question answering dataset for the ViTaB-A research project.
Configs
hitab: Derived from HiTab (10,670 samples)
fetaqa: Derived from FeTaQA (10,330 samples)
Usage
from datasets import load_dataset
hitab = load_dataset("raoanmol/ViTaB-A", "hitab")
fetaqa = load_dataset("raoanmol/ViTaB-A", "fetaqa")
Schema
Each sample contains:
Field
Type
Description
id
string
Unique identifier (e.g.… See the full description on the dataset page: https://huggingface.co/datasets/raoanmol/ViTaB-A.hromadske_corruptionmy-distiset-005084ec
Dataset Card for my-distiset-005084ec
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/Vittorio85/my-distiset-005084ec/raw/main/pipeline.yaml"
or explore the configuration:
distilabel pipeline info --config… See the full description on the dataset page: https://huggingface.co/datasets/Vittorio85/my-distiset-005084ec.