This is an understanding-focused SFT: only the language/understanding branch is optimized on the spatial corpus. The image-generation branch of the unified NEO-unify architecture is inherited unchanged from the base model (not further trained here).

Details


Base	`sensenova/SenseNova-U1-8B-MoT-SFT` (NEO-unify, `NEOChatModel`)
Data	SenseNova-SI-800K — 832K image+text spatial-intelligence samples (depth / distance / size / relative position / multi-view spatial relations)
Objective	understanding-only SFT (generation branch untouched)
Steps	≈183K (8×H100; lr 2e-4 constant; seq len 20480)
Precision	bfloat16

Built with the SenseNova-U1 training stack; recipe summarized above.

Usage

The model uses custom code (NEOChatModel); load with trust_remote_code=True. See the base model card for inference instructions — they apply unchanged.

License

Apache-2.0, inherited from the base model.

wchai/SenseNova-U1-8B-SI800K-SFT

SenseNova-U1-8B-SI800K-SFT

Details

Usage

License

wchai/
SenseNova-U1-8B-SI800K-SFT