datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
friend-bench
Can a model — or a human — tell how two people are related from a 20-second clip of how they interact?
🌐 Built on Seamless Interaction
FriendBench is a suite of benchmarks for social perception from thin-slice dyadic
interaction — inferring facts about two people's relationship from a brief clip of how they
interact, built on the Seamless Interaction
dataset. Each released set is a config of this repository.
🎧 Multi-modal — text, audio, and video for every clip
🎯 Objective label —… See the full description on the dataset page: https://huggingface.co/datasets/fluid-concepts/friend-bench.multimodal-peer-collaboration-samples
Multimodal Peer Collaboration Samples - Embodied Map Task with Two Camera Angles
Two non-experts collaborate to build working circuits under asymmetric information: the instructor has the manual, the student has the components, and synchronized audio and dual-camera video capture how shared understanding emerges.
▶ Watch the interactions · See Expert Instruction samples · Discuss the full collection
Sister collection: Expert Instruction, a teacher and a student in… See the full description on the dataset page: https://huggingface.co/datasets/fluid-concepts/multimodal-peer-collaboration-samples.multimodal-expert-instruction-samples
Multimodal Expert Instruction Samples - Musical Instrument Lessons with Channel-separated Audio and Video
A music teacher and a student work through two one-on-one lessons: both voices and both instruments on separate tracks, the student on camera, with the lesson plans, the instructions given to each side and both sides' post-lesson ratings alongside.
▶ Watch the lessons · See Peer Collaboration samples · Discuss the full collection
Sister collection: Peer Collaboration… See the full description on the dataset page: https://huggingface.co/datasets/fluid-concepts/multimodal-expert-instruction-samples.neuronpedia-sae-concepts
Neuronpedia SAE Concepts
Complete extraction of all individual concepts from every Sparse Autoencoder (SAE) released on Neuronpedia, plus all public features from Anthropic's Towards Monosemanticity (2023) and Scaling Monosemanticity (2024) papers.
Quick Start
from datasets import load_dataset
# Full Neuronpedia dataset (77M rows, streaming recommended)
ds = load_dataset("hbe/neuronpedia-sae-concepts", split="train", streaming=True)
# Unique concepts with essential… See the full description on the dataset page: https://huggingface.co/datasets/hbe/neuronpedia-sae-concepts.Related_Concepts_with_relevant_relasOA_Domain_Conceptssea-concepts-rawvisual_concepts