datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
smol-smoltalk-Interaction-SFT
Dataset Card for ReactiveAI/Smol-Smoltalk Interaction SFT
Derived from HuggingFaceTB/smol-smoltalk. Made for Interaction Supervised Fine-Tuning of Reactive Transformer
Proof-of-Concept models, especially RxT-Beta.
Dataset Details
Dataset Description
Reactive Transformers are processing only the single interactions in real-time and using Short-Term Memory to store information from previous interactions.
Before the model is able to use it's memory, it has to be… See the full description on the dataset page: https://huggingface.co/datasets/ReactiveAI/smol-smoltalk-Interaction-SFT.hle-react
AggAgent ReAct Rollouts - HLE
Dataset Description
AggAgent is an agentic aggregation framework that scales long-horizon agents at test time by sampling multiple parallel rollouts from a base agent and then aggregating their evidence and solutions. This dataset card releases the ReAct base rollouts that AggAgent consumes, i.e. single-agent trajectories produced before any aggregation step.
Each rollout was generated by running a ReAct-style deep-research… See the full description on the dataset page: https://huggingface.co/datasets/yoonsanglee/hle-react.Beta-Code
Reactive AI / Beta Code
Code-based pre-training corpus for RxT-Beta models, created from public & open datasets. Includes code in different programming languages.
Subsets are divided into short (< ~1024 tokens) and long (> ~1024 tokens) categories.
Original dataset
It's created from codeparrot datasets:
Python subsets from codeparrot/codeparrot-clean
other subsets from codeparrot/github-code-clean
ReactionSmiles
Reaction SMILES Dataset
A collated dataset of 3.4M unique chemical reaction SMILES strings compiled from multiple public sources for use in pre-training and fine-tuning chemical language models.
Reaction SMILES (Simplified Molecular Input Line Entry System) extend the standard SMILES notation to represent complete chemical reactions. They encode reactants, reagents/catalysts, and products in a single text string using the > delimiter:
reactants>reagents>products
For example:… See the full description on the dataset page: https://huggingface.co/datasets/Derify/ReactionSmiles.omnimcp_nextjs_react_architect_teaser
🔬 INSPECT THE DEEPSEEK-R1 REASONING CHAIN LIVE:
Zero hallucinations. Null syntax errors. 100% AST compiler validated.🌐 Live Interactive Reasoning & Code Inspector: https://emgena.com/trainingslager🎁 Claim your Free Starter Kit (Code: STARTER100): https://emgena.com/trainingslager🏷️ Launch Discount: Get 20 € OFF any 500-incident production suite with code LAUNCH20!
📜 Enterprise Compliance: EU AI Act Articles 50 & 53 certified • 100% DSGVO / GDPR clean • Commercial EULA… See the full description on the dataset page: https://huggingface.co/datasets/emgena/omnimcp_nextjs_react_architect_teaser.fineweb-2-pol-latest
ReactiveAI - FineWeb2 PL subset
This dataset is derived from polish subset of FineWeb2 by HuggingFace. Includes latest ~8.5M examples.
Original dataset description below
🥂 FineWeb2
A sparkling update with 1000s of languages
What is it?
This is the second iteration of the popular 🍷 FineWeb dataset, bringing high quality pretraining data to over 1000 🗣️ languages.
The 🥂 FineWeb2 dataset is fully reproducible, available under the permissive ODC-By… See the full description on the dataset page: https://huggingface.co/datasets/ReactiveAI/fineweb-2-pol-latest.deepsearchqa-react
AggAgent ReAct Rollouts - DeepSearchQA
Dataset Description
AggAgent is an agentic aggregation framework that scales long-horizon agents at test time by sampling multiple parallel rollouts from a base agent and then aggregating their evidence and solutions. This dataset card releases the ReAct base rollouts that AggAgent consumes, i.e. single-agent trajectories produced before any aggregation step.
Each rollout was generated by running a ReAct-style… See the full description on the dataset page: https://huggingface.co/datasets/yoonsanglee/deepsearchqa-react.RealStories-Micro-MRL
Dataset Card for ReactiveAI/RealStories-Micro-MRL
First synthetic Memory Reinforcement Learning dataset for Proof-of-Concept Reactive Transformer models.
Dataset is divided into subsets, used in different Curriculum Stage of MRL training - each subset have
different number of follow-up interactions, could use different strategy, and have train and validation
splits.
Subsets
steps-1: ~2300 train (~4600 interactions) / ~340 validation (~680 interactions) - Single-Step… See the full description on the dataset page: https://huggingface.co/datasets/ReactiveAI/RealStories-Micro-MRL.omnimcp_react_hydration_repair_teaser
🔬 INSPECT THE DEEPSEEK-R1 REASONING CHAIN LIVE:
Zero hallucinations. Null syntax errors. 100% AST compiler validated.🌐 Live Interactive Reasoning & Code Inspector: https://emgena.com/trainingslager🎁 Claim your Free Starter Kit (Code: STARTER100): https://emgena.com/trainingslager🏷️ Launch Discount: Get 20 € OFF any 500-incident production suite with code LAUNCH20!
📜 Enterprise Compliance: EU AI Act Articles 50 & 53 certified • 100% DSGVO / GDPR clean • Commercial EULA… See the full description on the dataset page: https://huggingface.co/datasets/emgena/omnimcp_react_hydration_repair_teaser.TinyStories-MRL
Dataset Card for ReactiveAI/TinyStories-MRL
Synthetic Memory Reinforcement Learning dataset for Proof-of-Concept Reactive Transformer models.
Dataset is divided into subsets, used in different Curriculum Stage of MRL training - each subset have
different number of follow-up interactions, could use different strategy, and have train and validation
splits.
After first experiments with MRL, we decided to abandon single step and two steps stages. That's because with single
step… See the full description on the dataset page: https://huggingface.co/datasets/ReactiveAI/TinyStories-MRL.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.smol-smoltalk-mini-Interaction-SFT
Dataset Card for ReactiveAI/Smol-Smoltalk-Mini Interaction SFT
Derived from HuggingFaceTB/smol-smoltalk (used 25% of train & test splits). Made for Interaction Supervised
Fine-Tuning of Reactive Transformer Proof-of-Concept models, especially RxT-Alpha-Mini (more info soon).
Full version available in ReactiveAI/smol-smoltalk-Interaction-SFT
Dataset Details
Dataset Description
Reactive Transformers are processing only the single interactions in… See the full description on the dataset page: https://huggingface.co/datasets/ReactiveAI/smol-smoltalk-mini-Interaction-SFT.TinyStories-Interaction-SFT
Dataset Card for ReactiveAI/TinyStories-Interaction-SFT
Improved version of ReactiveAI/TinyStories-mini-Interaction-SFT - about 4x more rows, improved generation prompt
and additional post-processing for more diverse dataset. Includes all examples from v1 Dataset and over 75k new ones, post-processed to include more random naming.
Dataset Details
Dataset Description
Interaction Supervised Fine-Tuning Dataset based on roneneldan/TinyStories dataset, made… See the full description on the dataset page: https://huggingface.co/datasets/ReactiveAI/TinyStories-Interaction-SFT.TinyStories-mini-Interaction-SFT
Dataset Card for ReactiveAI/TinyStories-mini-Interaction-SFT
Interaction Supervised Fine-Tuning Dataset based on roneneldan/TinyStories dataset, made for Reactive
Transformer second training stage Proof-of-Concept.
Full version available in ReactiveAI/TinyStories-Interaction-SFT
Dataset Details
Dataset Description
Curated by: Reactive AI
Language(s) (NLP): English
License: apache-2.0
Uses
This dataset is made for Supervised… See the full description on the dataset page: https://huggingface.co/datasets/ReactiveAI/TinyStories-mini-Interaction-SFT.AI-Knowledge-Chat-SMAT
Dataset Card for ReactiveAI/AI-Knowledge-Chat-SMAT
Conversational dataset for Supervised Memory Aware Training (SMAT) of Reactive Language Models (RxLM), containing dialogues
with AI/Data Science knowledge.
DOCS IN PROGRESS
Dataset Details
Dataset Description
Curated by: Adam Filipek / Reactive AI
Language(s) (NLP): English-only
License: Apache-2.0
Dataset Sources [optional]
Repository: [More Information Needed]
Paper [optional]:… See the full description on the dataset page: https://huggingface.co/datasets/ReactiveAI/AI-Knowledge-Chat-SMAT.researchrubrics-react
AggAgent ReAct Rollouts - ResearchRubrics
Dataset Description
AggAgent is an agentic aggregation framework that scales long-horizon agents at test time by sampling multiple parallel rollouts from a base agent and then aggregating their evidence and solutions. This dataset card releases the ReAct base rollouts that AggAgent consumes, i.e. single-agent trajectories produced before any aggregation step.
Each rollout was generated by running a ReAct-style… See the full description on the dataset page: https://huggingface.co/datasets/yoonsanglee/researchrubrics-react.healthbench-react
AggAgent ReAct Rollouts - HealthBench-Hard
Dataset Description
AggAgent is an agentic aggregation framework that scales long-horizon agents at test time by sampling multiple parallel rollouts from a base agent and then aggregating their evidence and solutions. This dataset card releases the ReAct base rollouts that AggAgent consumes, i.e. single-agent trajectories produced before any aggregation step.
Each rollout was generated by running a ReAct-style… See the full description on the dataset page: https://huggingface.co/datasets/yoonsanglee/healthbench-react.passkey-retrieval
ReactiveAI / passkey-retrieval (Interactions Format)
Conversational (in RxLM Interactions Format) retrieval (Passkey / Needle In a Haystack type) dataset, filtered and transformed from grimulkan/passkey-retrieval
Subsets
to-4k - 3-step instruct examples with first (context) message with up to 4k tokens
to-4k-reasoning - 3-step reasoning examples with first (context) query with up to 4k tokens and all the interaction (with reasoning) up to 8k tokens
to-8k - 3-step… See the full description on the dataset page: https://huggingface.co/datasets/ReactiveAI/passkey-retrieval.Open_Reaction_Data
ORDerly: Styrene Mizoroki-Heck RAG-Ready Dataset
This repository contains chemical reaction data formatted for Retrieval-Augmented Generation (RAG) systems.
The data is a processed version of the ORDerly benchmark, specifically focusing on reaction conditions and forward/retro prediction tasks.
Dataset Structure
The data is split into 10,000-row Parquet chunks to prevent Out-of-Memory (OOM) errors during ingestion into vector databases.
It includes:
orderly_condition:… See the full description on the dataset page: https://huggingface.co/datasets/Azzindani/Open_Reaction_Data.react-hook-form-sft-dataset
React Hook Form-SFT: Instruction-Tuning Dataset for React Hook Form v7.68
Dataset: summykai/react-hook-form-sft-datasetFormat: ChatML-style messages + structured metadataLibrary: React Hook Form v7.68.0 (release date: 2025-12-03)License: MIT (react-hook-form)
A research-grade supervised fine-tuning dataset that teaches models to write, debug, and explain React Hook Form patterns—covering both uncontrolled (register) and controlled (Controller) integrations, plus performance… See the full description on the dataset page: https://huggingface.co/datasets/summykai/react-hook-form-sft-dataset.cosmopedia-100k-Interaction-SFT
Dataset Card for ReactiveAI/cosmopedia-100k-Interaction-SFT
HuggingFaceTB/cosmopedia-100k dataset transformed into Reactive AI Interaction SFT format for stateful real-time
Reactive Language Models (RxLM).
Dataset Details
Dataset Description
The subset of Cosmopedia with 100k examples for Interaction Supervised Fine-Tuning, made
for Reactive Transformer models. We use it to train RxT-Beta generation.
Curated by: Adam Filipek & Reactive AI
Language(s) (NLP):… See the full description on the dataset page: https://huggingface.co/datasets/ReactiveAI/cosmopedia-100k-Interaction-SFT.coq-facts-props-proofs-gen0-v1
Dataset Name: Coq Facts, Propositions and Proofs
Dataset Description
The CoqFactsPropsProofs dataset aims to enhance Large Language Models'
(LLMs) proficiency in interpreting and generating Coq code by
providing a comprehensive collection of over 10,000 Coq source
files. It encompasses a wide array of propositions, proofs, and
definitions, enriched with metadata including source references and
licensing information. This dataset is designed to facilitate the
development… See the full description on the dataset page: https://huggingface.co/datasets/ReactorJet/coq-facts-props-proofs-gen0-v1.taskweft-fbd-react-train
taskweft-fbd-react-train
Intents and the IEC 61131-3 Function Block Diagrams that carry them out, as an
EditScore-shaped corpus: one root row per intent, three candidates per row (rank1 the
reference diagram, rank3 one that compiles and does the wrong thing, rank5 one the
compiler refuses), and one score row per candidate from the compiler's reference scan on three constructed input traces per row. Every row is
constructed from a template and a seed, so the labels are true by… See the full description on the dataset page: https://huggingface.co/datasets/chibifire/taskweft-fbd-react-train.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.WebApp1K-React-Generations
WebApp1K-React-Generations
A comprehensive evaluation dataset containing React component generations from 34 state-of-the-art AI models on 1,000 web application scenarios.
Dataset Description
This dataset extends the original WebApp1K-React benchmark by including actual code generations from major AI models. Each row contains a web application scenario along with generated React components from 34 different models and their test results.
Dataset Structure
1… See the full description on the dataset page: https://huggingface.co/datasets/onekq-ai/WebApp1K-React-Generations.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.WebApp1K-Duo-React-Generations
WebApp1K-Duo-React-Generations
A comprehensive evaluation dataset containing React component generations from 32 state-of-the-art AI models on 1,000 paired web application scenarios.
Dataset Description
This dataset extends the original WebApp1K-Duo-React benchmark by including actual code generations from major AI models. Each row contains a paired web application scenario (combining two functionalities) along with generated React components from 32 different models and… See the full description on the dataset page: https://huggingface.co/datasets/onekq-ai/WebApp1K-Duo-React-Generations.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.Search-Distill-5K-ReAct
TraceMind-Search-5K
TraceMind-Search-5K is a high-quality dataset featuring 5,000+ samples of search-augmented reasoning traces. It is specifically designed to train Small Language Models (SLMs) in the ReAct (Reasoning + Acting) pattern, focusing on precise information retrieval, noise filtering, and grounded synthesis.
Dataset Highlights
Total Samples: 4,997 entries in Parquet format.
File: train.parquet (2.7 MB).
Pattern: Strict adherence to the ReAct framework:
User… See the full description on the dataset page: https://huggingface.co/datasets/Salvor-Hardin/Search-Distill-5K-ReAct.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.