datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
fineweb_2_samples_hq
fineweb_2_samples_hq
FINEWEB2-HQ dataset
Dataset Structure
This dataset contains 5 JSONL files with a total size of 26415.31 MB.
Files:
ukr_Cyrl_sample_001.jsonl: 6163.40 MB
ron_Latn_sample_001.jsonl: 3739.69 MB
kor_Hang_sample_001.jsonl: 4120.89 MB
hin_Deva_sample_001.jsonl: 6681.96 MB
heb_Hebr_sample_001.jsonl: 5709.37 MB
Usage
from datasets import load_dataset
dataset = load_dataset("path/to/this/dataset")
Loading specific files… See the full description on the dataset page: https://huggingface.co/datasets/Mayank6255/fineweb_2_samples_hq.enterprise-agent-aa-samples
Dataset Card
Dataset Description
Enterprise Agent AA Samples contains three executable enterprise-agent scenarios grounded in frozen public data from UCI, the City of Chicago, and SEC Company Facts. The package combines bilingual task briefs, deterministic stateful environments, normalized tool-use trajectories, source-derived reference outputs, and binary rubric checks.
Task: enterprise tool-use and agent-trajectory evaluation
Languages: English and Chinese… See the full description on the dataset page: https://huggingface.co/datasets/LianeMarilin/enterprise-agent-aa-samples.nemo-stage1-50M-samples
NeMo Stage1 Pretraining Dataset - 50M Samples
This dataset contains 50 million text samples for NeMo model pretraining (Stage 1). The dataset is organized in chunks for efficient loading and processing.
Dataset Details
Total Samples: ~50,000,000
Format: JSONL (JSON Lines)
Structure: Each sample contains {"id": number, "text": "content"}
Chunks: 47 files (chunk_000.jsonl to chunk_046.jsonl)
Samples per chunk: ~1,000,000
Language: English
Task: Text generation pretraining… See the full description on the dataset page: https://huggingface.co/datasets/ssuresh/nemo-stage1-50M-samples.multimodal-video-annotation-samples
Video Annotation Samples – SuperviseLab
SuperviseLab provides professional video annotation data for training multimodal AI models. This public sample dataset demonstrates our annotation methodology and output quality across diverse video content categories.
Note: All visual assets in this dataset have been abstracted (pixelated mosaic) to protect source privacy. Uploader identity, original titles, and all identifiable metadata have been removed. This is a demonstration dataset… See the full description on the dataset page: https://huggingface.co/datasets/superviselab/multimodal-video-annotation-samples.Usenet-Corpus-1980-2013-Full-Samples
Usenet Corpus 1980–2013 — Full (Samples)
A small, browsable showcase sample of the Usenet Corpus 1980–2013 (cleaned)
dataset — long-form, pre-web Usenet posts. This repo is a free preview; the full,
commercially-licensed corpus (405.8M posts, 102.5B tokens) is at:
Full cleaned dataset (gated): https://huggingface.co/datasets/OwnedByDanes/Usenet-Corpus-1980-2013-Full
Threaded companion: https://huggingface.co/datasets/OwnedByDanes/Usenet-Corpus-1980-2013-Threaded… See the full description on the dataset page: https://huggingface.co/datasets/OwnedByDanes/Usenet-Corpus-1980-2013-Full-Samples.Usenet-Corpus-1980-2013-Threaded-Samples
Usenet Corpus 1980–2013 — Threaded (Samples)
A small, browsable showcase sample of the Usenet Corpus 1980–2013 — Threaded
dataset: Usenet posts reconstructed into conversations via thread_id,
thread_position, and thread_depth. This repo is a free preview; the full,
commercially-licensed corpus (405.6M posts, 190.8M threads, 102.5B tokens) is at:
Full threaded dataset (gated): https://huggingface.co/datasets/OwnedByDanes/Usenet-Corpus-1980-2013-Threaded
Cleaned (unthreaded)… See the full description on the dataset page: https://huggingface.co/datasets/OwnedByDanes/Usenet-Corpus-1980-2013-Threaded-Samples.aegis-multilingual-guard-dataset-v0.1-samples
AEGIS Multilingual Guard Dataset — Public Sample (100 per domain)
📋 This is a small public preview of the full AEGIS Multilingual Guard Dataset, a multilingual red-team / guardrail corpus. It contains 100 representative records per business domain (12 domains → 1,200 records) so you can explore the schema, languages and label balance before requesting the full dataset.
⚠️ Safety-research data. Records contain adversarial attack prompts (jailbreaks, prompt injections… See the full description on the dataset page: https://huggingface.co/datasets/YATAV-ENT/aegis-multilingual-guard-dataset-v0.1-samples.synthetic-self-correction-and-thinking-samples
Self Correction and Thinking
A seed library for training language models to reason with self-correction.
Teaches three reasoning behaviors -- catching your own errors, verifying correct answers, and rejecting false doubts -- across four domains, three difficulty tiers, and three reasoning modes. Also includes multi-turn user-correction conversations where the user actively corrects or challenges the assistant.
The structure at a glance
graph TB… See the full description on the dataset page: https://huggingface.co/datasets/sbussiso/synthetic-self-correction-and-thinking-samples.rose_code_samples
rose_code samples (pass@8 rollouts)
vLLM pass@8 samples on the CL-From-Nothing/rose_code train split (23,688 codeforces stdin/stdout
problems), scored by the deepcoder verifier (reward=1.0 iff all test cases pass).
Qwen3-1.7B/ — student model rollouts. 23,688 questions × 8 samples = 189,504 lines.
Qwen3-4B-Thinking-2507/ — teacher model rollouts.
Sampling: temperature 0.7, top_p 0.9, max_tokens 16384, 8 samples/question (pass@8).
Each cluster file holds a contiguous… See the full description on the dataset page: https://huggingface.co/datasets/CL-From-Nothing/rose_code_samples.Pidgin-QandA-data-samples
Pidgin Question-Answer Dataset (Sample)
Sample dataset: Nigerian Pidgin conversational Q&A for dialogue systems and language modeling
🤗 Hugging Face • 📊 Figshare • 🌐 Website • 📧 Contact
📋 Overview
The Pidgin Question-Answer Dataset (Sample) is a conversational corpus containing 1,462 question-answer pairs entirely in Nigerian Pidgin English. Created by Bytte AI through AI chatbot interactions with human validation, this sample dataset supports dialogue… See the full description on the dataset page: https://huggingface.co/datasets/Bytte-AI/Pidgin-QandA-data-samples.meetscribe-meeting-samples
MeetScribe Meeting Samples
Synthetic bilingual (EN/FA) enterprise meeting transcripts with labeled action items.
File
Language
Domain
operations_review_en
EN
Production / maintenance
operations_review_en.json
EN
JSON ASR (Whisper format)
safety_board_fa
FA
HSE safety board
procurement_sync_en
EN
Procurement / RFQ
maintenance_planning_fa
FA
Maintenance planning
Usage
python scripts/build_dataset.py
Generates meetings.jsonl with extracted… See the full description on the dataset page: https://huggingface.co/datasets/alirezaaminzadeh/meetscribe-meeting-samples.datagen-thor-samples
Datagen Thor Samples
Multilingual JSONL samples generated by datagen-thor.
ipda-golden-samples
IPDA Golden Samples (2AR + 1AR)
Golden samples for fine-tuning debate models on affirmative rebuttal speeches in IPDA format.
Dataset Description
874 high-quality samples for SFT training:
447 2AR (Second Affirmative Rebuttal)
427 1AR (First Affirmative Rebuttal)
Dataset Sources
Source
Count
Description
iter2_group_c
832
High-scoring (>=0.75) samples from GRPO iteration 2
augmented_claude-opus-4.5
20
Augmented debates generated by Claude Opus 4.5… See the full description on the dataset page: https://huggingface.co/datasets/dgonier/ipda-golden-samples.ipda-2ar-golden-samples
IPDA Golden Samples (2AR + 1AR)
Golden samples for fine-tuning debate models on affirmative rebuttal speeches in IPDA format.
Dataset Description
422 high-quality samples for SFT training:
260 2AR (Second Affirmative Rebuttal)
162 1AR (First Affirmative Rebuttal)
Dataset Sources
Model
2AR
1AR
Total
Claude Opus 4.5
100
50
150
GPT-5.2
100
50
150
Claude Sonnet
10
10
20
Claude Haiku
9
9
18
Qwen-ft (debate model)
19
19
38
Qwen-base
16
18
34… See the full description on the dataset page: https://huggingface.co/datasets/dgonier/ipda-2ar-golden-samples.DeepSeek-v3.1-reasoner-Distilled-math-samples
DeepSeek-V3.1 Distillation with NVIDIA Nemotron-Post-Training-Dataset-v2 (Math Subset)
The release of DeepSeek-V3.1 has attracted wide attention in the AI community. Its significant improvements in reasoning ability provide a new opportunity to explore optimization of domain-specific models. To investigate the potential of this model in complex mathematical reasoning tasks, I selected the math subset from NVIDIA’s newly released Nemotron-Post-Training-Dataset-v2 as seed problems and… See the full description on the dataset page: https://huggingface.co/datasets/Jackrong/DeepSeek-v3.1-reasoner-Distilled-math-samples.qwen-reasoning-samples-20260421_221240
Frontier-Class Synthetic Reasoning Samples
Dataset Description
10 synthetic reasoning examples generated with Qwen/Qwen3.6-35B-A3B via vLLM, using a structured prompt designed to elicit frontier-level (Opus 4.7 class) multi-phase reasoning.
Each example is gated through a quality filter that requires the reasoning trace to follow an explicit 6-phase structure (Understand → Decompose → Explore → Execute → Verify → Reflect) and to include an independent verification step.… See the full description on the dataset page: https://huggingface.co/datasets/himanshunakrani9/qwen-reasoning-samples-20260421_221240.CL-bench-samples
CL-bench samples by Mercor
Dataset Description
CL-bench is a benchmark for evaluating language models' context learning abilities.
Resolving tasks in CL-bench requires models to learn from the provided context, ranging from new domain-specific knowledge, rule systems, and complex procedures to laws derived from empirical data, rather than only relying on pre-trained knowledge.
Dataset Structure
Data Fields
Each sample in the dataset contains the… See the full description on the dataset page: https://huggingface.co/datasets/mercor/CL-bench-samples.code-review-findings-samples
Code Review Findings Samples
Curated synthetic examples for evaluating automated code review pipelines — especially the
AI Code Reviewer MCP stack built with
Qwen3.6-27B.
Each row contains a short code snippet, the analysis type, and a structured JSON output that
matches the review contract used by ImTamsi/qwen3.6-27b-code-reviewer.
Dataset structure
Column
Description
id
Stable sample identifier
analysis_type
review, bugs, security, performance… See the full description on the dataset page: https://huggingface.co/datasets/ImTamsi/code-review-findings-samples.industry-intelligence-graph-samples
Fodda Industry Intelligence — Graph Samples
Expert-curated knowledge graph slices for AI agents and LLM fine-tuning.
This dataset contains JSON-LD samples from Fodda's five core domain knowledge graphs — showing the top trending topics across Retail, Beauty, Sports, Fashion, and Culture.
These are slices of a much larger interconnected intelligence system.
What Fodda Is
Fodda is an AI context layer built on PSFK's 20+ years of editorial expertise. It structures… See the full description on the dataset page: https://huggingface.co/datasets/Fodda-ai/industry-intelligence-graph-samples.qwen-reasoning-samples-20260421_215219
Frontier-Class Synthetic Reasoning Samples
Dataset Description
1 synthetic reasoning examples generated with Qwen/Qwen3.6-35B-A3B via vLLM, using a structured prompt designed to elicit frontier-level (Opus 4.7 class) multi-phase reasoning.
Each example is gated through a quality filter that requires the reasoning trace to follow an explicit 6-phase structure (Understand → Decompose → Explore → Execute → Verify → Reflect) and to include an independent verification step.… See the full description on the dataset page: https://huggingface.co/datasets/himanshunakrani9/qwen-reasoning-samples-20260421_215219.code-workflow-samples
Code Workflow Samples
This sample shows paired developer workflow examples for reviewing prompt, code, test, error, and output structure before scoping a larger code dataset.
What This Shows
Input-output pairs from practical coding workflows
Metadata for task type, files, outputs, and review context
A compact view of schema consistency for code-centric examples
Dataset Specifications
Field
Value
Modality
Code I/O pairs
Domain… See the full description on the dataset page: https://huggingface.co/datasets/psdn-ai/code-workflow-samples.kush-v82-eval-samples
Kush v82 Eval Samples
Public evaluation samples for the Hotep Intelligence Kush v82 flagship model. Every entry is a prompt, a category, and a reference answer written in the target voice, so a reader can judge tone, framing, and factual grounding at the same time.
Try the live model in the hotep-intelligence-chat Space before or after reading these samples.
What This Dataset Is For
style and persona inspection
historical framing checks
sovereignty and… See the full description on the dataset page: https://huggingface.co/datasets/hotepfederales/kush-v82-eval-samples.qwen-reasoning-samples-20260421_220553
Frontier-Class Synthetic Reasoning Samples
Dataset Description
3 synthetic reasoning examples generated with Qwen/Qwen3.6-35B-A3B via vLLM, using a structured prompt designed to elicit frontier-level (Opus 4.7 class) multi-phase reasoning.
Each example is gated through a quality filter that requires the reasoning trace to follow an explicit 6-phase structure (Understand → Decompose → Explore → Execute → Verify → Reflect) and to include an independent verification step.… See the full description on the dataset page: https://huggingface.co/datasets/himanshunakrani9/qwen-reasoning-samples-20260421_220553.TACTBench-Samples
TACTBench Demonstration Samples
This repository contains five full-context demonstration examples from
TACTBench. It does not contain the TACT training set or the remaining hidden
TACTBench evaluation set. The samples use the same full-history representation
as the benchmark evaluation and illustrate direct correction, error
explanation, guided revision, clarification checking, affective feedback, and
retry elicitation.
Data
data/demo.jsonl: five complete… See the full description on the dataset page: https://huggingface.co/datasets/Taxonomy-Aligned-Conversational-Tutor/TACTBench-Samples.