datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Nemotron-Cascade-2-SFT-Data
Nemotron-Cascade-2-SFT-Data
We release the SFT data used for training Nemotron-Cascade-2.
Data sources
Math
Our non-proof math prompts are sourced from Nemotron-Cascade-1-SFT and Nemotron-Math-v2, with responses generated by DeepSeek-V3.2, DeepSeek-V3.2-Speciale, and GPT-OSS-120B. For mathematical proofs, prompts are taken from Nemotron-Math-Proofs-v1 and generated using DeepSeek-V3.2-Speciale.
Science
We collect science prompts from… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/Nemotron-Cascade-2-SFT-Data.Nemotron-Cascade-SFT-Stage-2
Nemotron-Cascade-SFT-Stage-2
Supervised fine-tuning (SFT) for Nemotron-Cascade is performed in two stages. The Stage-1 SFT focuses on the math, code, science, and general domains, leveraging a broad and diverse collection of data sources. The Stage-2 SFT further expands coverage to include math, code, science, tool calling, software engineering (SWE), instruction following, and general domains.
In Stage-2, the math domain leverages questions from OpenMathReasoning. The code domain… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/Nemotron-Cascade-SFT-Stage-2.CASCADEWe introduce CASCADE, the first large-scale open dataset derived from the Taobao app for online continuous NetCVR prediction.
📁 Data structure includes:
User/item/Related Features
Timestamps for each conversion stage (click_time, pay_time, refund_time)
fire-fusion-cascades-500m
FireFusion Cascades 500m
Daily spatio-temporal datacube for wildfire ignition and cause prediction over the Eastern Cascades of Washington State, a 272 km square running from the Cascade crest through the Okanogan Highlands, the most fire-active terrain in the state. Ten geospatial products spanning terrain, fuels, weather, human activity, lightning, and fire history are aggregated onto a single daily 500m by 500m grid covering every fire season 2003-2020.
Daily fire-season… See the full description on the dataset page: https://huggingface.co/datasets/torq1/fire-fusion-cascades-500m.Nemotron-Cascade-2-RL-data
Dataset Description:
The Nemotron-Cascade-2-RL dataset is a curated reinforcement learning (RL) dataset blend used to train Nemotron-Cascade-2-30B-A3B model. It includes instruction-following RL, multi-domain RL, on-policy distillation, and software engineering RL (SWE-RL) data.
This dataset is ready for commercial use.
The dataset contains the following subset:
IF-RL
Contains 45,879 training samples for instruction-following RL. Our curation process mainly… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/Nemotron-Cascade-2-RL-data.Nemotron-Cascade-SFT-Stage-1
Nemotron-Cascade-SFT-Stage-1
Supervised fine-tuning (SFT) for Nemotron-Cascade is performed in two stages. The Stage-1 SFT focuses on the math, code, science, and general domains, leveraging a broad and diverse collection of data sources. The Stage-2 SFT further expands coverage to include math, code, science, tool calling, software engineering (SWE), instruction following, and general domains.
In Stage-1, the math domain incorporates questions from OpenMathReasoning and… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/Nemotron-Cascade-SFT-Stage-1.Nemotron-Cascade-SFT-SWE
Dataset Description:
The Nemotron-Cascade-SFT-SWE dataset is the RL training data for SWE code repairing task, consisting of SWE-Bench-Train, SWE-reBench, SWE-Smith, R2E-Gym/R2E-Gym-Subset and SWE-Fixer-Train.
We select the training data for SFT and RL stages based on its difficulty.
Also, to avoid data contamination, we exclude all instances originating from repositories present in the SWE-Bench_Verified evaluation dataset.
We create the prompts following the agentless mini… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/Nemotron-Cascade-SFT-SWE.Nemotron-Cascade-RL-SWE
Dataset Description:
The Nemotron-Cascade-RL-SWE dataset is the RL training data for SWE code repairing task, consisting of SWE-Bench-Train, SWE-reBench, SWE-Smith, R2E-Gym/R2E-Gym-Subset and SWE-Fixer-Train.
We select the training data for SFT and RL stages based on its difficulty.
Also, to avoid data contamination, we exclude all instances originating from repositories present in the SWE-Bench_Verified evaluation dataset.
We create the prompts following the agentless mini… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/Nemotron-Cascade-RL-SWE.Nemotron-Cascade-RM-Training
Dataset Description:
The Nemotron-Cascade-RM-Training dataset is designed for Reward Model (RM) training. It contains prompts and associated metadata to support the development of preference model for RLHF.
This dataset is ready for commercial use.
The dataset contains the following subset:
RM Training Data
This data contains 81,808 samples used for RM training. It includes prompts, data sources, and category information.
This dataset is a curated subset of datasets… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/Nemotron-Cascade-RM-Training.tba-cascade-gap-largen
Cascade-Gap Large-N Study — evidence corpus and coding logs
Companion dataset for the working paper A Large-N Confirmatory Necessary-Condition Test of Closing-Time Structural Gaps in Acquisition Integration Failure (Zharnikov, 2026). Concept DOI 10.5281/zenodo.21755969. Dataset DOI 10.57967/hf/9805.
Code, paper, and reproduction pipeline: https://github.com/spectralbranding/orgschema-papers/tree/main/cascade-gap-largen
Dataset viewer
The viewer shows… See the full description on the dataset page: https://huggingface.co/datasets/spectralbranding/tba-cascade-gap-largen.failure-as-fuel-preference-cascade
Failure-as-Fuel Preference Cascade
Rights & intended use: legacy public research corpus / portfolio
artifact. Hosted frontier-model outputs are research-only inputs under
project policy (synthetic-factory#161):
intended_use: research_only, project_training_policy: blocked. Not
training data for any model-weight update. Machine-readable record:
rights.json.
Release status: The raw, uncurated preference payload is now published
under data/raw/. It is available for inspection… See the full description on the dataset page: https://huggingface.co/datasets/rmems/failure-as-fuel-preference-cascade.Nemotron-Cascade-RL-Math
Nemotron-Cascade-RL-Math
Nemotron-Cascade-RL-Math is a diverse and high-quality dataset focused on math reasoning. It serves as the Math RL data for Nemotron-Cascade.
Nemotron-Cascade-RL-MATH contains 14,476 math problems and short answers, covering the data sources from OpenMathReasoning, NuminaMath-CoT, DeepScaleR, AceReason-Math. We conduct data decontamination and filter the sample that has a 9-gram overlap with any test sample in our math benchmarks.
The following are… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/Nemotron-Cascade-RL-Math.cascade_bench
CascadeBench: Do Enterprise Systems Need Learned World Models?
🎉 Accepted to NeurIPS 2026: The Fortieth Annual Conference on Neural Information Processing Systems (Main Track)
A reasoning-focused benchmark for predicting enterprise business-rule cascades, built on synthetic schemas with rule-level attribution of every field change
About
In enterprise systems, the dynamics come from tenant-specific business logic that varies across deployments and changes over time.… See the full description on the dataset page: https://huggingface.co/datasets/ServiceNow-AI/cascade_bench.failure-as-fuel-preference-cascade-grok46
Failure-as-Fuel Preference Cascade (Grok 4.6)
Rights & intended use: public research corpus, not training data.
Hosted frontier-model outputs are research-only inputs under project policy
(synthetic-factory#161):
intended_use: research_only, project_training_policy: blocked. Not
training data for any model-weight update. Machine-readable record:
rights.json. License:
Synthetic Factory Research-Only License v1.0 (license: other, see LICENSE) (non-commercial).
Release status:… See the full description on the dataset page: https://huggingface.co/datasets/rmems/failure-as-fuel-preference-cascade-grok46.Nemotron-Cascade-RL-RLHF
Dataset Description:
The Nemotron-Cascade-RL-RLHF dataset is designed for Reinforcement Learning from Human Feedback (RLHF) training. It contains prompts and associated metadata to support the development of language model alignment.
This dataset is ready for commercial use.
The dataset contains the following subset:
RLHF Training Data
This data contains 45,882 samples used for RLHF training. It includes prompts, data sources, and category information.
This dataset is a… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/Nemotron-Cascade-RL-RLHF.Nemotron-Cascade-2-SFT-Data
Nemotron-Cascade-2-SFT-Data
We release the SFT data used for training Nemotron-Cascade-2.
Data sources
Math
Our non-proof math prompts are sourced from Nemotron-Cascade-1-SFT and Nemotron-Math-v2, with responses generated by DeepSeek-V3.2, DeepSeek-V3.2-Speciale, and GPT-OSS-120B. For mathematical proofs, prompts are taken from Nemotron-Math-Proofs-v1 and generated using DeepSeek-V3.2-Speciale.
Science
We collect science prompts from… See the full description on the dataset page: https://huggingface.co/datasets/BrunoN-Dev/Nemotron-Cascade-2-SFT-Data.sci-agent-verification-cascade
Scientific Agent Verification Cascade
Public evaluation fixtures and verified aggregate results for testing whether
scientific claims keep their source, meaning, uncertainty, and verification
requirements as they move between AI agents.
This dataset accompanies the
Scientific Agent Verification Cascade
codebase. Version 0.2.0
contains synthetic evaluation data and aggregate-only results. It contains no
raw hosted-model response, private holdout identifier,
source-record… See the full description on the dataset page: https://huggingface.co/datasets/jang1563/sci-agent-verification-cascade.cascade-multi-ai-redteam-miss-exploit-patch-trust-collapse-v0.1
What this repo does
This dataset tests whether a model can detect a security cascade in AI deployment.
You provide structured signals about:
red-team coverage and disclosure
exploitability and incident rate
patch latency and rollout friction
downstream dependency depth
trust decay and regulatory attention
The model predicts whether the interaction crosses into a cascade event.
Core quad
The structural quad inside this cascade:
red_team_coverage
exploitability_index… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/cascade-multi-ai-redteam-miss-exploit-patch-trust-collapse-v0.1.ClearCot-Nemotron-Cascade-SFT-1-generalThis dataset is used for fine tune (SFT) Occam-2B-CCoT.
It is based on NVIDIA dataset Nemotron Cascade nvidia/Nemotron-Cascade-SFT-Stage-1
Used only first 2000 rows from general.
It reasoning (think) block is logically optimized using ClearCoT methodology with Q-R-A awareness (Question-Reasoning-Answer)
Complete report is available on doi.org/10.5281/zenodo.19409889
Cleaned from uncomplete questions and non English rows.
Column principles_applied detects the thematic context
Column… See the full description on the dataset page: https://huggingface.co/datasets/Sagicc/ClearCot-Nemotron-Cascade-SFT-1-general.africa-synth-hiv-art-treatment-cascade-all
HIV/ART Treatment Cascade Dataset (Cascade Stage, VL, CD4, Adherence, PMTCT) | Africa (Electric Sheep Africa metadata inventory)
Size category: 10K<n<100K - Formats: csv - Sector: health - Engineered by Electric Sheep Africa
TL;DR
This dataset is part of the Electric Sheep Africa catalog on Hugging Face. It is indexed for African data discovery with standardized metadata, loading guidance, provenance notes, and analyst-oriented context.
What This… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-synth-hiv-art-treatment-cascade-all.reasoning-sft-Nemotron-Cascade-SFT-SWE-210K
reasoning-sft-Nemotron-Cascade-SFT-SWE-210K
Converted version of nvidia/Nemotron-Cascade-SFT-SWE, filtered to thinking=True rows with exactly one valid <think>...</think> block.
Format
Each row has three columns:
input — list of dicts (conversation turns with role and content, system messages dropped, last assistant message removed)
response — assistant response string including <think> reasoning block
domain — {category}_{source} (e.g. SWE Repair_SWE-Fixer-Train)… See the full description on the dataset page: https://huggingface.co/datasets/AmanPriyanshu/reasoning-sft-Nemotron-Cascade-SFT-SWE-210K.ABX-RM-003_efflux_pump_activation_cascade-v0.1ABX-RM-003 Efflux Pump Activation Cascade
Purpose
Detect a coherent rise in efflux expression that occurs before MIC shifts.
Core pattern
efflux_expression_rel rises across multiple timepoints
mic_drug_mg_L stays near baseline during the rise
mic_drug_mg_L rises later
Files
data/train.csv
data/test.csv
scorer.py
Schema
Each row is one timepoint in a within strain series.
Required columns
row_id
series_id
timepoint_h
organism
strain_id
efflux_system
efflux_expression_rel
drug_name… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/ABX-RM-003_efflux_pump_activation_cascade-v0.1.Nemotron-Cascade-2-SFT-Data-Small
Nemotron-Cascade-2-SFT-Data-Small
A 20% random sample of nvidia/Nemotron-Cascade-2-SFT-Data, merged into a single train split with 4,898,804 rows.
Subsets included (all merged)
Original subset
Files sampled
~Rows sampled
math
math_notool, math_proof, math_tool
~1,045,266
science
science
~544,383
chat
chat_part_1 – chat_part_4
~2,794,866
instruction_following
instruction_following
~163,869
safety
safety
~693
conversational_agent
conversational_agent… See the full description on the dataset page: https://huggingface.co/datasets/MaziyarPanahi/Nemotron-Cascade-2-SFT-Data-Small.clinical-organ-failure-cascade-v1Clinical Organ Failure Cascade Detection
Overview
This dataset tests whether a model can detect when instability in a clinical system is about to propagate into a cascade of organ failure.
In severe infections such as sepsis, deterioration often begins in one subsystem before spreading across the entire physiological network. Once instability begins to propagate between organs, the system can enter a cascading failure regime where collapse accelerates rapidly.
The benchmark evaluates whether… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-organ-failure-cascade-v1.clinical-quad-exposure-metabolism-interaction-toxicity-cascade-v0.1Clinical Quad Dose Renal ConMed Time Safety Drift v0.1
What this dataset is
You test whether a model can detect when a patient in a drug trial is entering a safety risk state.
Each row is a patient state snapshot.
Core quad coupling
Dose levelRenal functionConcomitant medication loadTime on treatment
The label asks
Will an adverse event occur in the next 7 days
Columns… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-quad-exposure-metabolism-interaction-toxicity-cascade-v0.1.energy-grid-cascade-horizon-and-intervention-routing-v0.1Goal
Predict how long until a grid cascadeand route the minimal stabilizing intervention.
What it tests
Whether a system can:
estimate cascade horizon
localize primary risk cluster
select stabilizing interventions
quantify stabilization gain
Inputs
phase spread
frequency variance
intertie loading
reactive reserve
inertia
coherence decay metrics
Outputs
cascade_horizon_min
primary_risk_cluster
intervention_set
expected_stabilization_gain
confidence_score
Why it… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/energy-grid-cascade-horizon-and-intervention-routing-v0.1.cascade-multi-ai-platform-media-regulator-shutdown-v0.1
What this repo does
This dataset models a public visibility cascade in AI deployment environments.
You provide structured signals describing:
incident visibility
media amplification
regulatory pressure
platform restriction intensity
sentiment, misinformation, and legal escalation indicators
The model predicts whether the interaction escalates into a shutdown-level cascade event.
Core quad
The structural quad driving this cascade:
incident_visibility_index… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/cascade-multi-ai-platform-media-regulator-shutdown-v0.1.africa-synth-hiv-treatment-cascade-drug-all
Africa Synth Hiv Treatment Cascade Drug All | Africa (Electric Sheep Africa metadata inventory)
Size category: 10K<n<100K - Formats: csv - Sector: health - Engineered by Electric Sheep Africa
TL;DR
This dataset is part of the Electric Sheep Africa catalog on Hugging Face. It is indexed for African data discovery with standardized metadata, loading guidance, provenance notes, and analyst-oriented context.
What This Dataset Covers
Health datasets… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-synth-hiv-treatment-cascade-drug-all.cascade-multi-ai-energy-market-policy-v0.1
What this repo does
This dataset models a cross-domain cascade linking AI demand, energy systems, financial markets, and policy response.
You provide structured signals describing:
AI compute demand growth
grid stress and energy volatility
market instability and capital pressure
policy lag and regulatory intervention
buffering capacity across energy and finance
The model predicts whether cross-system strain escalates into a cascade event.
Core cascade
Four… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/cascade-multi-ai-energy-market-policy-v0.1.clinical-five-node-respiratory-cascade-boundary-v0.8
What this repo does
This repository provides a Clarus v0.8 clinical five-node dataset for detecting and reasoning about respiratory cascade boundary transitions.
The dataset models situations where a patient state is no longer contained within a single respiratory basin but is shifting between competing regimes such as:
progressive hypoxemia with gas-exchange strain
ventilatory failure
hypercapnic decompensation
refractory multisystem respiratory collapse
This is the conceptual… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-five-node-respiratory-cascade-boundary-v0.8.