cat
Datasets
All datasets matching “cat”catalog
Mesh-LLM Catalog
This dataset is the Hugging Face-backed catalog for Mesh-LLM.
The runtime catalog entries live under entries/**/*.json. The Dataset Viewer
uses catalog_rows.jsonl, a flat generated table with one row per model variant.
The catalog deliberately excludes raw blob URLs. Entries should resolve to
Hugging Face repositories and canonical Mesh refs.
xr-motion-dataset-catalogue
XR Motion Dataset Catalogue
Overview
The XR Motion Dataset Catalogue, accompanying our paper "Navigating the Kinematic Maze: A Comprehensive Guide to XR Motion Dataset Standards," standardizes and simplifies access to Extended Reality (XR) motion datasets. The catalogue represents our initiative to streamline the usage of kinematic data in XR research by aligning various datasets to a consistent format and structure.
Dataset Specifications
All datasets in this… See the full description on the dataset page: https://huggingface.co/datasets/cschell/xr-motion-dataset-catalogue.catholic-resources
Vietnamese Catholic resources by v-bible
Data Structure
calendar: Generated Liturgical calendars using
v-bible/js-sdk.
misc/proper-names.json: Name translation from
ktcgkpv.org, generated by
v-bible/bible-scraper.
liturgical: Liturgical data from
The Lectionary for Mass (1998/2002 USA Edition),
compiled by Felix Just, S.J., Ph.D., and generated by
v-bible/bible-scraper.
books/bible: Generated Bible markdown data.
books/catechism-books: Official catechism… See the full description on the dataset page: https://huggingface.co/datasets/v-bible/catholic-resources.montok
MonTok: A Suite of Monolingual Tokenizers
This is a set of monolingual tokenizers for 98 languages. For each language, there are Unigram, BPE, and SuperBPE tokenizers, ranging in vocabulary size from around 6k to over 200k.
Training Details
Training Data
All tokenizers are trained on samples of the data used to the train the Goldfish language models.
The tokenizers were either trained on scaled or unscaled data. This refers to whether the models are trained on… See the full description on the dataset page: https://huggingface.co/datasets/catherinearnett/montok.cats-imagevbvr-latent-cache-832x832x33f-t2v-only
VBVR Latent Cache (832×832 × 33f, Wan2.2-TI2V-5B VAE + UMT5-XXL)
Pre-encoded latent cache for the
Video-Reason/VBVR-Dataset
geometric / logical reasoning video corpus, prepared for Equilibrium Matching
(EqM) post-training of Wan-AI/Wan2.2-TI2V-5B-Diffusers on AWS Trainium2.
This is a working cache, not a primary dataset. It exists to skip the
~5 s/sample VAE+T5 encode cost during training. The original videos +
prompts live in the upstream VBVR-Dataset repo.
Source →… See the full description on the dataset page: https://huggingface.co/datasets/Central-Cat/vbvr-latent-cache-832x832x33f-t2v-only.
