datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
react-shadcn-codex
React Shadcn Codex Dataset
Description
The React Shadcn Codex is a curated collection of over 3,000 React components that utilize shadcn, Framer Motion, and Lucide React. This dataset provides a valuable resource for developers looking to understand and implement modern React UI components with these popular libraries.
Content
The dataset includes:
3,000+ React components using shadcn UI
Components with Framer Motion animations
Usage examples of Lucide React… See the full description on the dataset page: https://huggingface.co/datasets/valentin-marquez/react-shadcn-codex.Nemotron-Math-Proofs-v1
Nemotron-Math-Proofs-v1
Paper: Nemotron-Math: Efficient Long-Context Distillation of Mathematical Reasoning from Multi-Mode SupervisionCode: https://github.com/NVIDIA/NeMo-SkillsDocumentation: Nemotron-MathProofs-v1 documentation
Dataset Description:
Nemotron-Math-Proofs-v1 is a large-scale mathematical reasoning dataset containing ~580k natural language proof problems, ~550k formalizations into theorem statements in Lean 4, and ~900k model-generated reasoning… See the full description on the dataset page: https://huggingface.co/datasets/ReactorJet/Nemotron-Math-Proofs-v1.dbbench_sft_dataset_react
DBBench SFT Dataset (ReAct Format — AgentBench Compatible)
Overview
Synthetic SFT dataset for DBBench (AgentBench, ICLR 2024).
All tables, data, and queries are independently generated to avoid test data leakage.
Format
ReAct text format matching the AgentBench DBBench evaluation protocol:
[user] System prompt (Action: Operation / Action: Answer instructions)
[agent] Ok.
[user] Question + table name + column headers
[agent] Thinking + Action: Operation +… See the full description on the dataset page: https://huggingface.co/datasets/u-10bei/dbbench_sft_dataset_react.dbbench_sft_dataset_react_v2
DBBench SFT Dataset (ReAct Format — AgentBench Compatible)
Overview
Synthetic SFT dataset for DBBench (AgentBench, ICLR 2024).
All tables, data, and queries are independently generated to avoid test data leakage.
Format
ReAct text format matching the AgentBench DBBench evaluation protocol:
[user] System prompt (Action: Operation / Action: Answer instructions)
[agent] Ok.
[user] Question + table name + column headers
[agent] Thinking + Action: Operation +… See the full description on the dataset page: https://huggingface.co/datasets/u-10bei/dbbench_sft_dataset_react_v2.dbbench_sft_dataset_react_v4
DBBench SFT Dataset (ReAct Format — AgentBench Compatible)
Overview
Synthetic SFT dataset for DBBench (AgentBench, ICLR 2024).
All tables, data, and queries are independently generated to avoid test data leakage.
Format
ReAct text format matching the AgentBench DBBench evaluation protocol:
[user] System prompt (Action: Operation / Action: Answer instructions)
[agent] Ok.
[user] Question + table name + column headers
[agent] Thinking + Action: Operation +… See the full description on the dataset page: https://huggingface.co/datasets/u-10bei/dbbench_sft_dataset_react_v4.dbbench_sft_dataset_react_v3
DBBench SFT Dataset (ReAct Format — AgentBench Compatible)
Overview
Synthetic SFT dataset for DBBench (AgentBench, ICLR 2024).
All tables, data, and queries are independently generated to avoid test data leakage.
Format
ReAct text format matching the AgentBench DBBench evaluation protocol:
[user] System prompt (Action: Operation / Action: Answer instructions)
[agent] Ok.
[user] Question + table name + column headers
[agent] Thinking + Action: Operation +… See the full description on the dataset page: https://huggingface.co/datasets/u-10bei/dbbench_sft_dataset_react_v3.