datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
ego10k-vjepa-latents
Ego10k V-JEPA Latents Dataset
This dataset contains compressed, highly-informative Video Joint Embedding Predictive Architecture (V-JEPA) latents extracted from Ego-centric industrial manufacturing videos.
Dataset Structure
The dataset is partitioned into roughly 1GB .parquet chunks using PyArrow.
Data Source and Preprocessing
The latent embeddings in this dataset were systematically extracted from the Ego10k Master Dataset provided by build.ai. The… See the full description on the dataset page: https://huggingface.co/datasets/rookierufus/ego10k-vjepa-latents.VJEPA-LATENTS-L2NORMsokoban-10k-vjepa2-tokenizedepic-kitchens-vjepacs2-10k-vjepa2-latents-300
CS2-10k V-JEPA2 latent cache (300 matches)
Frozen facebook/vjepa2-vitl-fpc64-256 embeddings of single-POV Counter-Strike 2
gameplay, from 300 matches of RekaAI/CS2-10k
(mirage + dust2). This is the training substrate for the
scale300 hierarchical world model.
Rebuilding it from source takes ~82 hours of wall-clock (elapsed_min 4942.7),
almost all of it network-bound, which is why it is published here.
Contents
file
shape / rows
notes
latents.npy
[6,942… See the full description on the dataset page: https://huggingface.co/datasets/cbctr/cs2-10k-vjepa2-latents-300.epic-kitchens-vjepavjepa2-temporal-order-blindspots
V-JEPA2 Temporal Order Blind Spots
This dataset documents blind spots for the pretrained video world model facebook/vjepa2-vith-fpc64-256.
The model produces nearly identical embeddings for videos whose temporal order has been severely corrupted, indicating weak sensitivity to temporal directionality and causal motion structure.
Model Tested
Model name: facebook/vjepa2-vith-fpc64-256Type: Self-supervised video world model (JEPA-style joint embedding predictive… See the full description on the dataset page: https://huggingface.co/datasets/Nuntea/vjepa2-temporal-order-blindspots.Vjepa_mamba_datasetsokoban-10k-vjepa2-tokenized-shardsvjepa-results