sections
Datasets
All datasets matching “sections”riskroll-sec-10k-10q-sections
Riskroll: SEC 10-K and 10-Q sections as clean text
Need it fresh, filtered or via API? This free file is a snapshot (10-K/10-Q sections up to the last refresh), last updated 2026-09-24.
Insidewell on Apify ($0.004 per insider transaction): pulls today's SEC Form 4 trades for your own watchlist, filtered by buy/sell and size, with cluster-buy alerts on a schedule.
Using it at work? Commercial license + support (from $49/year): invoice, PDF licence certificate, named… See the full description on the dataset page: https://huggingface.co/datasets/CyberMax-tools/riskroll-sec-10k-10q-sections.indian-legal-sections-bns-bnss-bsa-2023
🏛️ Indian Legal Sections — BNS · BNSS · BSA 2023
The First Structured, Unified JSON Dataset of Modern Indian Criminal Law
📖 Dataset Summary
This dataset contains 1,059 fully structured and verified sections extracted, parsed, and unified from India's three landmark criminal justice reform acts passed in December 2023. These three acts together replaced the colonial-era Indian Penal Code (IPC, 1860), the Code of Criminal Procedure… See the full description on the dataset page: https://huggingface.co/datasets/GSMS-B/indian-legal-sections-bns-bnss-bsa-2023.sections
Dataset Card for "sections"
More Information needed
Coffee_leaves_sections_FO
Dataset Card for coffee_leaves_anomalib_2
This is a FiftyOne dataset with 35962 samples.
Installation
If you haven't already, install FiftyOne:
pip install -U fiftyone
Usage
import fiftyone as fo
from fiftyone.utils.huggingface import load_from_hub
# Load the dataset
# Note: other available arguments include 'max_samples', etc
dataset = load_from_hub("pjramg/Coffee_leaves_sections_FO")
# Launch the App
session = fo.launch_app(dataset)… See the full description on the dataset page: https://huggingface.co/datasets/pjramg/Coffee_leaves_sections_FO.stranger_sections_2wikipedia-sections
Dataset Card for Wikipedia Sections
This dataset contains pairs and triplets that can be used to train and finetune Sentence Transformer embedding models. The dataset originates from Dor et al., and was downloaded from this download link.
Notably, the "anchor" column contains sentences from Wikipedia, wheras the "positive" column contains other sentences from the same section. The "negative" column contains sentences from other sections.
Dataset Subsets… See the full description on the dataset page: https://huggingface.co/datasets/sentence-transformers/wikipedia-sections.