Model Hub
Browse PQC-verified AI models, datasets, and tools
Boasting over 10,000 hours of cumulative data and 1 million+ clips, it ranks as the largest open-source embodied intelligence dataset in the industry. Compared with other datasets, it has the following advantages: Ample Data Volume & Strong Generalization Each skill is supported by sufficient data, collected from over 3,000 households and nearly 10,000 distinct fine-grained targets. It avoids simple repetitions and ensures robust generalization. Authentic Scenarios & Focused… See the full description on the dataset page: https://huggingface.co/datasets/ad1t7a/10Kh-RealOmin-OpenData.
Dataset Card for "winogrande" Dataset Summary WinoGrande is a new collection of 44k problems, inspired by Winograd Schema Challenge (Levesque, Davis, and Morgenstern 2011), but adjusted to improve the scale and robustness against the dataset-specific bias. Formulated as a fill-in-a-blank task with binary options, the goal is to choose the right option for a given sentence which requires commonsense reasoning. Supported Tasks and Leaderboards More Information… See the full description on the dataset page: https://huggingface.co/datasets/allenai/winogrande.
15T token dataset of cleaned English web data. Deduplicated and filtered from CommonCrawl, outperforms C4 and RefinedWeb for LLM pretraining.
SAGE-10k SAGE-10k is a large-scale interactive indoor scene dataset featuring realistic layouts, generated by the agentic-driven pipeline introduced in "SAGE: Scalable Agentic 3D Scene Generation for Embodied AI". The dataset contains 10,000 diverse scenes spanning 50 room types and styles, along with 565K uniquely generated 3D objects. 🔑 Key Features SAGE-10k integrates a wide variety of scenes, and particularly, preserves small items for… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/SAGE-10k.
Dataset Card for IFEval Dataset Summary This dataset contains the prompts used in the Instruction-Following Eval (IFEval) benchmark for large language models. It contains around 500 "verifiable instructions" such as "write in more than 400 words" and "mention the keyword of AI at least 3 times" which can be verified by heuristics. To load the dataset, run: from datasets import load_dataset ifeval = load_dataset("google/IFEval") Supported Tasks and… See the full description on the dataset page: https://huggingface.co/datasets/google/IFEval.