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factorjepa-cosmos-future-adapter
Aaypom/factorjepa-cosmos-future-adapter
factorjepa-cosmos-future-adapter is a video-to-video model from Aaypom. Use it for the video-to-video task on the model card, and read the license before you ship it in a product. It is set up for pytorch.
This repository contains the small trainable adapter that maps frozen FactorJEPA future tokens into NVIDIA Cosmos continuous video latents. It predicts two future latent slots; a separately encoded last-context-frame…
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At a glance
- Task
- Video-to-Video
- Library
- pytorch
- Access
- Public
- Created
- Sep 20, 2026
- Updated
- Sep 20, 2026
- SHA
- 23834e42
Model card
From the Hugging Face model README
FactorJEPA to Cosmos future-latent adapter
This repository contains the small trainable adapter that maps frozen FactorJEPA future tokens into NVIDIA Cosmos continuous video latents. It predicts two future latent slots; a separately encoded last-context-frame anchor is prepended only for causal 4k+1 decoding. It does not contain the upstream FactorJEPA or Cosmos weights.
- Base FactorJEPA checkpoint:
anonymousML123/factorjepa-outputs/outputs/full/vjepa_2_1_vitg_1B/train/m09c_surgery_3stage_DI_diheavy_encoder/m09c_ckpt_best.pt - Cosmos tokenizer:
nvidia/Cosmos-0.1-Tokenizer-CV4x8x8 - Best/latest metric payload:
metrics/best.json - Training code:
experiments/jepa_cosmosin the FactorJEPA repository.
- Task
- Video-to-Video
- Library
- pytorch
- Created
- Sep 20, 2026
- Updated
- Sep 20, 2026