datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Blockchain-Sensitive-Detect-Data
Blockchain-Sensitive-Detect-Data
English README
复旦大学附属儿科医院-区块链敏感信息检测项目的多模态完整测试数据集。
项目仓库：https://github.com/anyangsong/Blockchain-Sensitive-Detect
数据集：https://huggingface.co/datasets/anyangsong/Blockchain-Sensitive-Detect-Data
checkpoints：https://huggingface.co/anyangsong/Blockchain-Sensitive-Detect-Checkpoints
数据以原始文件夹组织，覆盖文本、音频、图像与视频等样本。
该仓库不提供统一的 CSV、Parquet 或 JSONL 清单；类别信息主要由目录名和文件名携带。
内容警告： 数据集包含辱骂、性内容、暴力、政治相关内容、误导性医疗信息、欺诈信息。使用者应仅在具备适当访问控制、伦理审查和当地法律依据的环境中处理这些内容。… See the full description on the dataset page: https://huggingface.co/datasets/anyangsong/Blockchain-Sensitive-Detect-Data.Align-Anything-Instruction-100K-zh
Dataset Card for Align-Anything-Instruction-100K-zh
[🏠 Homepage]
[🤗 Instruction-Dataset-100K(en)]
[🤗 Instruction-Dataset-100K(zh)]
[🤗 Align-Anything Datasets]
Instruction-Dataset-100K(zh)
Highlights
Data sources:
Firefly (47.8%),
COIG (2.9%),
and our meticulously constructed QA pairs (49.3%).
100K QA pairs (zh): 104,550 meticulously crafted instructions, selected and polished from various Chinese datasets… See the full description on the dataset page: https://huggingface.co/datasets/PKU-Alignment/Align-Anything-Instruction-100K-zh.Align-Anything-Instruction-100K
Dataset Card for Align-Anything-Instruction-100K
[🏠 Homepage]
[🤗 Instruction-Dataset-100K(en)]
[🤗 Instruction-Dataset-100K(zh)]
[🤗 Align-Anything Datasets]
Highlights
Data sources:
PKU-SafeRLHF QA ,
DialogSum,
Empathetic,
Instruction-Wild,
and Alpaca.
100K QA pairs: By leveraging GPT-4 to annotate meticulously refined instructions, we obtain 105,333 QA pairs.… See the full description on the dataset page: https://huggingface.co/datasets/PKU-Alignment/Align-Anything-Instruction-100K.souslab-us-restaurant-menus
Souslab — US Restaurant Menus
A structured sample of the Souslab US restaurant menu dataset: real restaurants, real menu items, real prices — normalized into a clean schema you can train on or analyze directly.
This sample is published openly under CC-BY-NC-4.0 for research and non-commercial evaluation. The full dataset — 449,000+ US restaurants and 44.3M+ menu items, refreshed continuously with chain-level aggregation — is available via the Souslab API under commercial… See the full description on the dataset page: https://huggingface.co/datasets/AnyStackLabsdev/souslab-us-restaurant-menus.sonnylm_generic
SonnyLM Chat Dataset
Training data for SonnyLM — a tiny character LLM that talks like Sonny:
my fat, long-haired orange cat who is lazy, extremely vocal, hates being picked up,
has furry "grinch paws," sleeps only on dirty laundry, and loves tuna and mom (mom because she brings the tuna).
Same shape and method as GuppyLM,
re-skinned from a generic fish to one very specific cat.
Who is Sonny
Trait
How it shows up
Fat & long-furred
"substantial,"… See the full description on the dataset page: https://huggingface.co/datasets/AnyaAl/sonnylm_generic.Llama-2-7b-chat-finetune
plagas y enfermedades en el cultivo del tomate Dataset 1000
Dataset de 1000 instrucciones sobre la plagas y enfermedades en el cultivo del tomate.
Uso
from datasets import load_dataset
dataset = load_dataset("anyerg21/plagas-enfermedades-tomate-1000")
Estructura
instruction: Pregunta sobre el cultivo del tomate
input: Campo vacio
output: Respuesta
category: Categoria tematica
question_type: Tipo de pregunta
difficulty: Nivel de dificultad
Ejemplo… See the full description on the dataset page: https://huggingface.co/datasets/anyerg21/Llama-2-7b-chat-finetune.formal-anytime-valid-stats
Formal-AVS: A Lean Benchmark for Anytime-Valid Confidence-Sequence Theorem Proving
60 Lean 4 theorem targets on anytime-valid confidence sequences across four families (Howard-Ramdas, betting, Whitehouse vector, asymptotic CLT).
Benchmark Structure
60 targets grouped into tiers T0-T3 (pre-evaluation) and categories T4-T5 (empirical)
7 drafters evaluated across single-shot, agentic, and unbounded modes
14 Aristotle sessions (unbounded refinement)
Headline Results… See the full description on the dataset page: https://huggingface.co/datasets/neurips-2026-avs-bench/formal-anytime-valid-stats.anycrap
ANYCRAP: Absurdist AI-Generated Product Catalog
A dataset of 120,000+ AI-generated absurdist and creative product concepts, collected over ~1 year from the ANYCRAP catalog platform. Products range from gentle wordplay to surreal absurdism, with multilingual names, AI-generated descriptions and images, engagement data, manual category labels, and AI-powered quality scores.
What's in it
Config
Size
Description
full
126K
All products — names, descriptions… See the full description on the dataset page: https://huggingface.co/datasets/kafked/anycrap.formal-anytime-valid-stats
Formal-AVS: A Lean Benchmark for Anytime-Valid Confidence-Sequence Theorem Proving
60 Lean 4 theorem targets on anytime-valid confidence sequences across four families (Howard-Ramdas, betting, Whitehouse vector, asymptotic CLT).
Benchmark Structure
60 targets grouped into tiers T0-T3 (pre-evaluation) and categories T4-T5 (empirical)
48-target evaluated slate (headline drafter sweeps)
14 Aristotle sessions (unbounded refinement)
Headline Results (pass@5 on… See the full description on the dataset page: https://huggingface.co/datasets/athanor-ai/formal-anytime-valid-stats.AnythingLLM