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Dataset · Hugging Face

dingshizhe/molmo-ae-cc12m-latents

CC12M latents — VGT-AE with a frozen SigLIP2 (Molmo) encoder Pre-encoded CC12M images as (32, 16, 16) float16 latents, paired with their captions. WebDataset format: 1097 tars, each member a <key>.npy + <key>.txt pair. samples 6,836,022 shards 1097 latent shape (32, 16, 16) float16 input resolution 512 px encoder VGTAE_Siglip2, siglip2vit_frozen_stage2 (50K steps) ViT Molmo SigLIP2-base/patch16, frozen through both stages decoder (for reference)… See the full description on the dataset page: https://huggingface.co/datasets/dingshizhe/molmo-ae-cc12m-latents.

Author / organizationdingshizhe
License (as declared)cc-by-4.0
Downloads341 (as reported by Hugging Face)
Likes1
Created12 August 2026
Last updated at source12 August 2026
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