datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
razavi-benchRazavi-bench
An expert-curated benchmark for analog-design reasoning.
Razavi-bench packages the question-answer assessments from Behzad Razavi's
Analog Design Experiments With AI Part 1 and Part 2 into a clean
one-task-per-directory benchmark. The tasks probe whether a model can reason
about MOS devices, small-signal circuits, feedback, oscillators, comparators,
dividers, LNAs, TIAs, and LC oscillators.
Each task directory keeps only the benchmark prompt, figure, and curated… See the full description on the dataset page: https://huggingface.co/datasets/Arcadia-2026/razavi-bench.MathNet
Quick Start · Overview · Tasks · Comparison · Dataset Stats · Data Sources · Pipeline · Schema · License · Citation
This is the official MathNet v0. A larger version v1 will be uploaded soon (more countires, problems and richer metadata). Schema is stable but field values may be revised in v1.
Quick start
from datasets import load_dataset
# Default: all problems
ds = load_dataset("ShadenA/MathNet", split="train")
# Or a specific country / competition-body config
arg… See the full description on the dataset page: https://huggingface.co/datasets/archya/MathNet.ARC_AGI_V1_ULTRAarc-agi-2
ARC-AGI-2 Few-Shot Conversations
ARC-AGI-2 is a benchmark of 1,000 public training tasks and 120 public evaluation tasks for assessing reasoning systems. This repository packages the public tasks into a Hugging Face–friendly format with:
canonical/original arc-agi 2 train/evaluation splits
Parquet shards for fast downloads & streaming
per-example PNG renderings of every grid (demonstration and test)
text prompts & full conversations ready for LLM fine-tuning
Dataset… See the full description on the dataset page: https://huggingface.co/datasets/vincentkoc/arc-agi-2.azure-architecture-vqa
Azure Architecture Visual Question Answering Dataset
A comprehensive visual question answering (VQA) dataset for fine-tuning vision language models to become Azure Cloud Solution Architects. Created from the Azure Architecture Center.
Dataset Description
This dataset contains Q&A pairs paired with Azure architecture diagrams, designed for fine-tuning vision language models (like Qwen 3.5 VL) to understand and reason about cloud architecture patterns.
Source… See the full description on the dataset page: https://huggingface.co/datasets/thegovind/azure-architecture-vqa.